---
OA_place: publisher
OA_type: hybrid
_id: '9526'
abstract:
- lang: eng
  text: DNA methylation and histone H1 mediate transcriptional silencing of genes
    and transposable elements, but how they interact is unclear. In plants and animals
    with mosaic genomic methylation, functionally mysterious methylation is also common
    within constitutively active housekeeping genes. Here, we show that H1 is enriched
    in methylated sequences, including genes, of Arabidopsis thaliana, yet this enrichment
    is independent of DNA methylation. Loss of H1 disperses heterochromatin, globally
    alters nucleosome organization, and activates H1-bound genes, but only weakly
    de-represses transposable elements. However, H1 loss strongly activates transposable
    elements hypomethylated through mutation of DNA methyltransferase MET1. Hypomethylation
    of genes also activates antisense transcription, which is modestly enhanced by
    H1 loss. Our results demonstrate that H1 and DNA methylation jointly maintain
    transcriptional homeostasis by silencing transposable elements and aberrant intragenic
    transcripts. Such functionality plausibly explains why DNA methylation, a well-known
    mutagen, has been maintained within coding sequences of crucial plant and animal
    genes.
article_processing_charge: No
article_type: original
author:
- first_name: Jaemyung
  full_name: Choi, Jaemyung
  last_name: Choi
- first_name: David B.
  full_name: Lyons, David B.
  last_name: Lyons
- first_name: M. Yvonne
  full_name: Kim, M. Yvonne
  last_name: Kim
- first_name: Jonathan D.
  full_name: Moore, Jonathan D.
  last_name: Moore
- first_name: Daniel
  full_name: Zilberman, Daniel
  id: 6973db13-dd5f-11ea-814e-b3e5455e9ed1
  last_name: Zilberman
  orcid: 0000-0002-0123-8649
citation:
  ama: Choi J, Lyons DB, Kim MY, Moore JD, Zilberman D. DNA methylation and histone
    H1 jointly repress transposable elements and aberrant intragenic transcripts.
    <i>Molecular Cell</i>. 2020;77(2):310-323.e7. doi:<a href="https://doi.org/10.1016/j.molcel.2019.10.011">10.1016/j.molcel.2019.10.011</a>
  apa: Choi, J., Lyons, D. B., Kim, M. Y., Moore, J. D., &#38; Zilberman, D. (2020).
    DNA methylation and histone H1 jointly repress transposable elements and aberrant
    intragenic transcripts. <i>Molecular Cell</i>. Elsevier. <a href="https://doi.org/10.1016/j.molcel.2019.10.011">https://doi.org/10.1016/j.molcel.2019.10.011</a>
  chicago: Choi, Jaemyung, David B. Lyons, M. Yvonne Kim, Jonathan D. Moore, and Daniel
    Zilberman. “DNA Methylation and Histone H1 Jointly Repress Transposable Elements
    and Aberrant Intragenic Transcripts.” <i>Molecular Cell</i>. Elsevier, 2020. <a
    href="https://doi.org/10.1016/j.molcel.2019.10.011">https://doi.org/10.1016/j.molcel.2019.10.011</a>.
  ieee: J. Choi, D. B. Lyons, M. Y. Kim, J. D. Moore, and D. Zilberman, “DNA methylation
    and histone H1 jointly repress transposable elements and aberrant intragenic transcripts,”
    <i>Molecular Cell</i>, vol. 77, no. 2. Elsevier, p. 310–323.e7, 2020.
  ista: Choi J, Lyons DB, Kim MY, Moore JD, Zilberman D. 2020. DNA methylation and
    histone H1 jointly repress transposable elements and aberrant intragenic transcripts.
    Molecular Cell. 77(2), 310–323.e7.
  mla: Choi, Jaemyung, et al. “DNA Methylation and Histone H1 Jointly Repress Transposable
    Elements and Aberrant Intragenic Transcripts.” <i>Molecular Cell</i>, vol. 77,
    no. 2, Elsevier, 2020, p. 310–323.e7, doi:<a href="https://doi.org/10.1016/j.molcel.2019.10.011">10.1016/j.molcel.2019.10.011</a>.
  short: J. Choi, D.B. Lyons, M.Y. Kim, J.D. Moore, D. Zilberman, Molecular Cell 77
    (2020) 310–323.e7.
date_created: 2021-06-08T06:37:09Z
date_published: 2020-01-16T00:00:00Z
date_updated: 2024-10-16T12:14:37Z
day: '16'
department:
- _id: DaZi
doi: 10.1016/j.molcel.2019.10.011
extern: '1'
external_id:
  pmid:
  - '31732458'
intvolume: '        77'
issue: '2'
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://doi.org/10.1016/j.molcel.2019.10.011
month: '01'
oa: 1
oa_version: Published Version
page: 310-323.e7
pmid: 1
publication: Molecular Cell
publication_identifier:
  eissn:
  - 1097-4164
  issn:
  - 1097-2765
publication_status: published
publisher: Elsevier
quality_controlled: '1'
scopus_import: '1'
status: public
title: DNA methylation and histone H1 jointly repress transposable elements and aberrant
  intragenic transcripts
type: journal_article
user_id: 0043cee0-e5fc-11ee-9736-f83bc23afbf0
volume: 77
year: '2020'
...
---
_id: '9573'
abstract:
- lang: eng
  text: It is a classical fact that for any ε>0, a random permutation of length n=(1+ε)k2/4
    typically contains a monotone subsequence of length k. As a far-reaching generalization,
    Alon conjectured that a random permutation of this same length n is typically
    k-universal, meaning that it simultaneously contains every pattern of length k.
    He also made the simple observation that for n=O(k2logk), a random length-n permutation
    is typically k-universal. We make the first significant progress towards Alon's
    conjecture by showing that n=2000k2loglogk suffices.
article_processing_charge: No
article_type: original
arxiv: 1
author:
- first_name: Xiaoyu
  full_name: He, Xiaoyu
  last_name: He
- first_name: Matthew Alan
  full_name: Kwan, Matthew Alan
  id: 5fca0887-a1db-11eb-95d1-ca9d5e0453b3
  last_name: Kwan
  orcid: 0000-0002-4003-7567
citation:
  ama: He X, Kwan MA. Universality of random permutations. <i>Bulletin of the London
    Mathematical Society</i>. 2020;52(3):515-529. doi:<a href="https://doi.org/10.1112/blms.12345">10.1112/blms.12345</a>
  apa: He, X., &#38; Kwan, M. A. (2020). Universality of random permutations. <i>Bulletin
    of the London Mathematical Society</i>. Wiley. <a href="https://doi.org/10.1112/blms.12345">https://doi.org/10.1112/blms.12345</a>
  chicago: He, Xiaoyu, and Matthew Alan Kwan. “Universality of Random Permutations.”
    <i>Bulletin of the London Mathematical Society</i>. Wiley, 2020. <a href="https://doi.org/10.1112/blms.12345">https://doi.org/10.1112/blms.12345</a>.
  ieee: X. He and M. A. Kwan, “Universality of random permutations,” <i>Bulletin of
    the London Mathematical Society</i>, vol. 52, no. 3. Wiley, pp. 515–529, 2020.
  ista: He X, Kwan MA. 2020. Universality of random permutations. Bulletin of the
    London Mathematical Society. 52(3), 515–529.
  mla: He, Xiaoyu, and Matthew Alan Kwan. “Universality of Random Permutations.” <i>Bulletin
    of the London Mathematical Society</i>, vol. 52, no. 3, Wiley, 2020, pp. 515–29,
    doi:<a href="https://doi.org/10.1112/blms.12345">10.1112/blms.12345</a>.
  short: X. He, M.A. Kwan, Bulletin of the London Mathematical Society 52 (2020) 515–529.
date_created: 2021-06-21T06:23:42Z
date_published: 2020-06-01T00:00:00Z
date_updated: 2023-02-23T14:01:23Z
day: '01'
doi: 10.1112/blms.12345
extern: '1'
external_id:
  arxiv:
  - '1911.12878'
intvolume: '        52'
issue: '3'
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://arxiv.org/abs/1911.12878
month: '06'
oa: 1
oa_version: Preprint
page: 515-529
publication: Bulletin of the London Mathematical Society
publication_identifier:
  eissn:
  - 1469-2120
  issn:
  - 0024-6093
publication_status: published
publisher: Wiley
quality_controlled: '1'
scopus_import: '1'
status: public
title: Universality of random permutations
type: journal_article
user_id: 6785fbc1-c503-11eb-8a32-93094b40e1cf
volume: 52
year: '2020'
...
---
_id: '9576'
abstract:
- lang: eng
  text: In 1989, Rota made the following conjecture. Given n bases B1,…,Bn in an n-dimensional
    vector space V⁠, one can always find n disjoint bases of V⁠, each containing exactly
    one element from each Bi (we call such bases transversal bases). Rota’s basis
    conjecture remains wide open despite its apparent simplicity and the efforts of
    many researchers (e.g., the conjecture was recently the subject of the collaborative
    “Polymath” project). In this paper we prove that one can always find (1/2−o(1))n
    disjoint transversal bases, improving on the previous best bound of Ω(n/logn)⁠.
    Our results also apply to the more general setting of matroids.
article_processing_charge: No
article_type: original
arxiv: 1
author:
- first_name: Matija
  full_name: Bucić, Matija
  last_name: Bucić
- first_name: Matthew Alan
  full_name: Kwan, Matthew Alan
  id: 5fca0887-a1db-11eb-95d1-ca9d5e0453b3
  last_name: Kwan
  orcid: 0000-0002-4003-7567
- first_name: Alexey
  full_name: Pokrovskiy, Alexey
  last_name: Pokrovskiy
- first_name: Benny
  full_name: Sudakov, Benny
  last_name: Sudakov
citation:
  ama: Bucić M, Kwan MA, Pokrovskiy A, Sudakov B. Halfway to Rota’s basis conjecture.
    <i>International Mathematics Research Notices</i>. 2020;2020(21):8007-8026. doi:<a
    href="https://doi.org/10.1093/imrn/rnaa004">10.1093/imrn/rnaa004</a>
  apa: Bucić, M., Kwan, M. A., Pokrovskiy, A., &#38; Sudakov, B. (2020). Halfway to
    Rota’s basis conjecture. <i>International Mathematics Research Notices</i>. Oxford
    University Press. <a href="https://doi.org/10.1093/imrn/rnaa004">https://doi.org/10.1093/imrn/rnaa004</a>
  chicago: Bucić, Matija, Matthew Alan Kwan, Alexey Pokrovskiy, and Benny Sudakov.
    “Halfway to Rota’s Basis Conjecture.” <i>International Mathematics Research Notices</i>.
    Oxford University Press, 2020. <a href="https://doi.org/10.1093/imrn/rnaa004">https://doi.org/10.1093/imrn/rnaa004</a>.
  ieee: M. Bucić, M. A. Kwan, A. Pokrovskiy, and B. Sudakov, “Halfway to Rota’s basis
    conjecture,” <i>International Mathematics Research Notices</i>, vol. 2020, no.
    21. Oxford University Press, pp. 8007–8026, 2020.
  ista: Bucić M, Kwan MA, Pokrovskiy A, Sudakov B. 2020. Halfway to Rota’s basis conjecture.
    International Mathematics Research Notices. 2020(21), 8007–8026.
  mla: Bucić, Matija, et al. “Halfway to Rota’s Basis Conjecture.” <i>International
    Mathematics Research Notices</i>, vol. 2020, no. 21, Oxford University Press,
    2020, pp. 8007–26, doi:<a href="https://doi.org/10.1093/imrn/rnaa004">10.1093/imrn/rnaa004</a>.
  short: M. Bucić, M.A. Kwan, A. Pokrovskiy, B. Sudakov, International Mathematics
    Research Notices 2020 (2020) 8007–8026.
date_created: 2021-06-21T08:12:30Z
date_published: 2020-11-01T00:00:00Z
date_updated: 2023-02-23T14:01:30Z
day: '01'
doi: 10.1093/imrn/rnaa004
extern: '1'
external_id:
  arxiv:
  - '1810.07462'
intvolume: '      2020'
issue: '21'
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: http://arxiv-export-lb.library.cornell.edu/abs/1810.07462
month: '11'
oa: 1
oa_version: Preprint
page: 8007-8026
publication: International Mathematics Research Notices
publication_identifier:
  eissn:
  - 1687-0247
  issn:
  - 1073-7928
publication_status: published
publisher: Oxford University Press
quality_controlled: '1'
scopus_import: '1'
status: public
title: Halfway to Rota’s basis conjecture
type: journal_article
user_id: 6785fbc1-c503-11eb-8a32-93094b40e1cf
volume: 2020
year: '2020'
...
---
OA_place: publisher
OA_type: hybrid
_id: '9577'
abstract:
- lang: eng
  text: An n-vertex graph is called C-Ramsey if it has no clique or independent set
    of size Clogn⁠. All known constructions of Ramsey graphs involve randomness in
    an essential way, and there is an ongoing line of research towards showing that
    in fact all Ramsey graphs must obey certain “richness” properties characteristic
    of random graphs. Motivated by an old problem of Erd̋s and McKay, recently Narayanan,
    Sahasrabudhe, and Tomon conjectured that for any fixed C, every n-vertex C-Ramsey
    graph induces subgraphs of Θ(n2) different sizes. In this paper we prove this
    conjecture.
article_processing_charge: No
article_type: original
arxiv: 1
author:
- first_name: Matthew Alan
  full_name: Kwan, Matthew Alan
  id: 5fca0887-a1db-11eb-95d1-ca9d5e0453b3
  last_name: Kwan
  orcid: 0000-0002-4003-7567
- first_name: Benny
  full_name: Sudakov, Benny
  last_name: Sudakov
citation:
  ama: Kwan MA, Sudakov B. Ramsey graphs induce subgraphs of quadratically many sizes.
    <i>International Mathematics Research Notices</i>. 2020;2020(6):1621–1638. doi:<a
    href="https://doi.org/10.1093/imrn/rny064">10.1093/imrn/rny064</a>
  apa: Kwan, M. A., &#38; Sudakov, B. (2020). Ramsey graphs induce subgraphs of quadratically
    many sizes. <i>International Mathematics Research Notices</i>. Oxford University
    Press. <a href="https://doi.org/10.1093/imrn/rny064">https://doi.org/10.1093/imrn/rny064</a>
  chicago: Kwan, Matthew Alan, and Benny Sudakov. “Ramsey Graphs Induce Subgraphs
    of Quadratically Many Sizes.” <i>International Mathematics Research Notices</i>.
    Oxford University Press, 2020. <a href="https://doi.org/10.1093/imrn/rny064">https://doi.org/10.1093/imrn/rny064</a>.
  ieee: M. A. Kwan and B. Sudakov, “Ramsey graphs induce subgraphs of quadratically
    many sizes,” <i>International Mathematics Research Notices</i>, vol. 2020, no.
    6. Oxford University Press, pp. 1621–1638, 2020.
  ista: Kwan MA, Sudakov B. 2020. Ramsey graphs induce subgraphs of quadratically
    many sizes. International Mathematics Research Notices. 2020(6), 1621–1638.
  mla: Kwan, Matthew Alan, and Benny Sudakov. “Ramsey Graphs Induce Subgraphs of Quadratically
    Many Sizes.” <i>International Mathematics Research Notices</i>, vol. 2020, no.
    6, Oxford University Press, 2020, pp. 1621–1638, doi:<a href="https://doi.org/10.1093/imrn/rny064">10.1093/imrn/rny064</a>.
  short: M.A. Kwan, B. Sudakov, International Mathematics Research Notices 2020 (2020)
    1621–1638.
date_created: 2021-06-21T08:30:12Z
date_published: 2020-03-01T00:00:00Z
date_updated: 2024-10-16T12:20:07Z
day: '01'
doi: 10.1093/imrn/rny064
extern: '1'
external_id:
  arxiv:
  - '1711.02937'
intvolume: '      2020'
issue: '6'
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://doi.org/10.1093/imrn/rny064
month: '03'
oa: 1
oa_version: Published Version
page: 1621–1638
publication: International Mathematics Research Notices
publication_identifier:
  eissn:
  - 1687-0247
  issn:
  - 1073-7928
publication_status: published
publisher: Oxford University Press
quality_controlled: '1'
scopus_import: '1'
status: public
title: Ramsey graphs induce subgraphs of quadratically many sizes
type: journal_article
user_id: 0043cee0-e5fc-11ee-9736-f83bc23afbf0
volume: 2020
year: '2020'
...
---
_id: '9578'
abstract:
- lang: eng
  text: How long a monotone path can one always find in any edge-ordering of the complete
    graph Kn? This appealing question was first asked by Chvátal and Komlós in 1971,
    and has since attracted the attention of many researchers, inspiring a variety
    of related problems. The prevailing conjecture is that one can always find a monotone
    path of linear length, but until now the best known lower bound was n2/3-o(1).
    In this paper we almost close this gap, proving that any edge-ordering of the
    complete graph contains a monotone path of length n1-o(1).
article_processing_charge: No
article_type: original
arxiv: 1
author:
- first_name: Matija
  full_name: Bucić, Matija
  last_name: Bucić
- first_name: Matthew Alan
  full_name: Kwan, Matthew Alan
  id: 5fca0887-a1db-11eb-95d1-ca9d5e0453b3
  last_name: Kwan
  orcid: 0000-0002-4003-7567
- first_name: Alexey
  full_name: Pokrovskiy, Alexey
  last_name: Pokrovskiy
- first_name: Benny
  full_name: Sudakov, Benny
  last_name: Sudakov
- first_name: Tuan
  full_name: Tran, Tuan
  last_name: Tran
- first_name: Adam Zsolt
  full_name: Wagner, Adam Zsolt
  last_name: Wagner
citation:
  ama: Bucić M, Kwan MA, Pokrovskiy A, Sudakov B, Tran T, Wagner AZ. Nearly-linear
    monotone paths in edge-ordered graphs. <i>Israel Journal of Mathematics</i>. 2020;238(2):663-685.
    doi:<a href="https://doi.org/10.1007/s11856-020-2035-7">10.1007/s11856-020-2035-7</a>
  apa: Bucić, M., Kwan, M. A., Pokrovskiy, A., Sudakov, B., Tran, T., &#38; Wagner,
    A. Z. (2020). Nearly-linear monotone paths in edge-ordered graphs. <i>Israel Journal
    of Mathematics</i>. Springer. <a href="https://doi.org/10.1007/s11856-020-2035-7">https://doi.org/10.1007/s11856-020-2035-7</a>
  chicago: Bucić, Matija, Matthew Alan Kwan, Alexey Pokrovskiy, Benny Sudakov, Tuan
    Tran, and Adam Zsolt Wagner. “Nearly-Linear Monotone Paths in Edge-Ordered Graphs.”
    <i>Israel Journal of Mathematics</i>. Springer, 2020. <a href="https://doi.org/10.1007/s11856-020-2035-7">https://doi.org/10.1007/s11856-020-2035-7</a>.
  ieee: M. Bucić, M. A. Kwan, A. Pokrovskiy, B. Sudakov, T. Tran, and A. Z. Wagner,
    “Nearly-linear monotone paths in edge-ordered graphs,” <i>Israel Journal of Mathematics</i>,
    vol. 238, no. 2. Springer, pp. 663–685, 2020.
  ista: Bucić M, Kwan MA, Pokrovskiy A, Sudakov B, Tran T, Wagner AZ. 2020. Nearly-linear
    monotone paths in edge-ordered graphs. Israel Journal of Mathematics. 238(2),
    663–685.
  mla: Bucić, Matija, et al. “Nearly-Linear Monotone Paths in Edge-Ordered Graphs.”
    <i>Israel Journal of Mathematics</i>, vol. 238, no. 2, Springer, 2020, pp. 663–85,
    doi:<a href="https://doi.org/10.1007/s11856-020-2035-7">10.1007/s11856-020-2035-7</a>.
  short: M. Bucić, M.A. Kwan, A. Pokrovskiy, B. Sudakov, T. Tran, A.Z. Wagner, Israel
    Journal of Mathematics 238 (2020) 663–685.
date_created: 2021-06-21T13:24:35Z
date_published: 2020-07-01T00:00:00Z
date_updated: 2023-02-23T14:01:35Z
day: '01'
doi: 10.1007/s11856-020-2035-7
extern: '1'
external_id:
  arxiv:
  - '1809.01468'
intvolume: '       238'
issue: '2'
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://arxiv.org/abs/1809.01468
month: '07'
oa: 1
oa_version: Preprint
page: 663-685
publication: Israel Journal of Mathematics
publication_identifier:
  eissn:
  - 1565-8511
  issn:
  - 0021-2172
publication_status: published
publisher: Springer
quality_controlled: '1'
scopus_import: '1'
status: public
title: Nearly-linear monotone paths in edge-ordered graphs
type: journal_article
user_id: 6785fbc1-c503-11eb-8a32-93094b40e1cf
volume: 238
year: '2020'
...
---
_id: '9581'
abstract:
- lang: eng
  text: "We show that for any  \U0001D45B  divisible by 3, almost all order-  \U0001D45B
    \ Steiner triple systems have a perfect matching (also known as a parallel class
    or resolution class). In fact, we prove a general upper bound on the number of
    perfect matchings in a Steiner triple system and show that almost all Steiner
    triple systems essentially attain this maximum. We accomplish this via a general
    theorem comparing a uniformly random Steiner triple system to the outcome of the
    triangle removal process, which we hope will be useful for other problems. Our
    methods can also be adapted to other types of designs; for example, we sketch
    a proof of the theorem that almost all Latin squares have transversals."
article_processing_charge: No
article_type: original
arxiv: 1
author:
- first_name: Matthew Alan
  full_name: Kwan, Matthew Alan
  id: 5fca0887-a1db-11eb-95d1-ca9d5e0453b3
  last_name: Kwan
  orcid: 0000-0002-4003-7567
citation:
  ama: Kwan MA. Almost all Steiner triple systems have perfect matchings. <i>Proceedings
    of the London Mathematical Society</i>. 2020;121(6):1468-1495. doi:<a href="https://doi.org/10.1112/plms.12373">10.1112/plms.12373</a>
  apa: Kwan, M. A. (2020). Almost all Steiner triple systems have perfect matchings.
    <i>Proceedings of the London Mathematical Society</i>. Wiley. <a href="https://doi.org/10.1112/plms.12373">https://doi.org/10.1112/plms.12373</a>
  chicago: Kwan, Matthew Alan. “Almost All Steiner Triple Systems Have Perfect Matchings.”
    <i>Proceedings of the London Mathematical Society</i>. Wiley, 2020. <a href="https://doi.org/10.1112/plms.12373">https://doi.org/10.1112/plms.12373</a>.
  ieee: M. A. Kwan, “Almost all Steiner triple systems have perfect matchings,” <i>Proceedings
    of the London Mathematical Society</i>, vol. 121, no. 6. Wiley, pp. 1468–1495,
    2020.
  ista: Kwan MA. 2020. Almost all Steiner triple systems have perfect matchings. Proceedings
    of the London Mathematical Society. 121(6), 1468–1495.
  mla: Kwan, Matthew Alan. “Almost All Steiner Triple Systems Have Perfect Matchings.”
    <i>Proceedings of the London Mathematical Society</i>, vol. 121, no. 6, Wiley,
    2020, pp. 1468–95, doi:<a href="https://doi.org/10.1112/plms.12373">10.1112/plms.12373</a>.
  short: M.A. Kwan, Proceedings of the London Mathematical Society 121 (2020) 1468–1495.
date_created: 2021-06-22T06:35:16Z
date_published: 2020-12-01T00:00:00Z
date_updated: 2023-02-23T14:01:43Z
day: '01'
doi: 10.1112/plms.12373
extern: '1'
external_id:
  arxiv:
  - '1611.02246'
intvolume: '       121'
issue: '6'
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://arxiv.org/abs/1611.02246
month: '12'
oa: 1
oa_version: Preprint
page: 1468-1495
publication: Proceedings of the London Mathematical Society
publication_identifier:
  eissn:
  - 1460-244X
  issn:
  - 0024-6115
publication_status: published
publisher: Wiley
quality_controlled: '1'
scopus_import: '1'
status: public
title: Almost all Steiner triple systems have perfect matchings
type: journal_article
user_id: 6785fbc1-c503-11eb-8a32-93094b40e1cf
volume: 121
year: '2020'
...
---
_id: '9582'
abstract:
- lang: eng
  text: The problem of finding dense induced bipartite subgraphs in H-free graphs
    has a long history, and was posed 30 years ago by Erdős, Faudree, Pach and Spencer.
    In this paper, we obtain several results in this direction. First we prove that
    any H-free graph with minimum degree at least d contains an induced bipartite
    subgraph of minimum degree at least cH log d/log log d, thus nearly confirming
    one and proving another conjecture of Esperet, Kang and Thomassé. Complementing
    this result, we further obtain optimal bounds for this problem in the case of
    dense triangle-free graphs, and we also answer a question of Erdœs, Janson, Łuczak
    and Spencer.
article_processing_charge: No
article_type: original
arxiv: 1
author:
- first_name: Matthew Alan
  full_name: Kwan, Matthew Alan
  id: 5fca0887-a1db-11eb-95d1-ca9d5e0453b3
  last_name: Kwan
  orcid: 0000-0002-4003-7567
- first_name: Shoham
  full_name: Letzter, Shoham
  last_name: Letzter
- first_name: Benny
  full_name: Sudakov, Benny
  last_name: Sudakov
- first_name: Tuan
  full_name: Tran, Tuan
  last_name: Tran
citation:
  ama: Kwan MA, Letzter S, Sudakov B, Tran T. Dense induced bipartite subgraphs in
    triangle-free graphs. <i>Combinatorica</i>. 2020;40(2):283-305. doi:<a href="https://doi.org/10.1007/s00493-019-4086-0">10.1007/s00493-019-4086-0</a>
  apa: Kwan, M. A., Letzter, S., Sudakov, B., &#38; Tran, T. (2020). Dense induced
    bipartite subgraphs in triangle-free graphs. <i>Combinatorica</i>. Springer. <a
    href="https://doi.org/10.1007/s00493-019-4086-0">https://doi.org/10.1007/s00493-019-4086-0</a>
  chicago: Kwan, Matthew Alan, Shoham Letzter, Benny Sudakov, and Tuan Tran. “Dense
    Induced Bipartite Subgraphs in Triangle-Free Graphs.” <i>Combinatorica</i>. Springer,
    2020. <a href="https://doi.org/10.1007/s00493-019-4086-0">https://doi.org/10.1007/s00493-019-4086-0</a>.
  ieee: M. A. Kwan, S. Letzter, B. Sudakov, and T. Tran, “Dense induced bipartite
    subgraphs in triangle-free graphs,” <i>Combinatorica</i>, vol. 40, no. 2. Springer,
    pp. 283–305, 2020.
  ista: Kwan MA, Letzter S, Sudakov B, Tran T. 2020. Dense induced bipartite subgraphs
    in triangle-free graphs. Combinatorica. 40(2), 283–305.
  mla: Kwan, Matthew Alan, et al. “Dense Induced Bipartite Subgraphs in Triangle-Free
    Graphs.” <i>Combinatorica</i>, vol. 40, no. 2, Springer, 2020, pp. 283–305, doi:<a
    href="https://doi.org/10.1007/s00493-019-4086-0">10.1007/s00493-019-4086-0</a>.
  short: M.A. Kwan, S. Letzter, B. Sudakov, T. Tran, Combinatorica 40 (2020) 283–305.
date_created: 2021-06-22T06:42:26Z
date_published: 2020-04-01T00:00:00Z
date_updated: 2023-02-23T14:01:45Z
day: '01'
doi: 10.1007/s00493-019-4086-0
extern: '1'
external_id:
  arxiv:
  - '1810.12144'
intvolume: '        40'
issue: '2'
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://arxiv.org/abs/1810.12144
month: '04'
oa: 1
oa_version: Preprint
page: 283-305
publication: Combinatorica
publication_identifier:
  eissn:
  - 1439-6912
  issn:
  - 0209-9683
publication_status: published
publisher: Springer
quality_controlled: '1'
scopus_import: '1'
status: public
title: Dense induced bipartite subgraphs in triangle-free graphs
type: journal_article
user_id: 6785fbc1-c503-11eb-8a32-93094b40e1cf
volume: 40
year: '2020'
...
---
DOAJ_listed: '1'
OA_place: publisher
OA_type: gold
_id: '9583'
abstract:
- lang: eng
  text: We show that for any n divisible by 3, almost all order-n Steiner triple systems
    admit a decomposition of almost all their triples into disjoint perfect matchings
    (that is, almost all Steiner triple systems are almost resolvable).
article_number: e39
article_processing_charge: No
article_type: original
author:
- first_name: Asaf
  full_name: Ferber, Asaf
  last_name: Ferber
- first_name: Matthew Alan
  full_name: Kwan, Matthew Alan
  id: 5fca0887-a1db-11eb-95d1-ca9d5e0453b3
  last_name: Kwan
  orcid: 0000-0002-4003-7567
citation:
  ama: Ferber A, Kwan MA. Almost all Steiner triple systems are almost resolvable.
    <i>Forum of Mathematics</i>. 2020;8. doi:<a href="https://doi.org/10.1017/fms.2020.29">10.1017/fms.2020.29</a>
  apa: Ferber, A., &#38; Kwan, M. A. (2020). Almost all Steiner triple systems are
    almost resolvable. <i>Forum of Mathematics</i>. Cambridge University Press. <a
    href="https://doi.org/10.1017/fms.2020.29">https://doi.org/10.1017/fms.2020.29</a>
  chicago: Ferber, Asaf, and Matthew Alan Kwan. “Almost All Steiner Triple Systems
    Are Almost Resolvable.” <i>Forum of Mathematics</i>. Cambridge University Press,
    2020. <a href="https://doi.org/10.1017/fms.2020.29">https://doi.org/10.1017/fms.2020.29</a>.
  ieee: A. Ferber and M. A. Kwan, “Almost all Steiner triple systems are almost resolvable,”
    <i>Forum of Mathematics</i>, vol. 8. Cambridge University Press, 2020.
  ista: Ferber A, Kwan MA. 2020. Almost all Steiner triple systems are almost resolvable.
    Forum of Mathematics. 8, e39.
  mla: Ferber, Asaf, and Matthew Alan Kwan. “Almost All Steiner Triple Systems Are
    Almost Resolvable.” <i>Forum of Mathematics</i>, vol. 8, e39, Cambridge University
    Press, 2020, doi:<a href="https://doi.org/10.1017/fms.2020.29">10.1017/fms.2020.29</a>.
  short: A. Ferber, M.A. Kwan, Forum of Mathematics 8 (2020).
date_created: 2021-06-22T09:12:23Z
date_published: 2020-11-03T00:00:00Z
date_updated: 2024-10-16T12:26:40Z
day: '03'
ddc:
- '510'
doi: 10.1017/fms.2020.29
extern: '1'
external_id:
  pmid:
  - '1907.06744'
file:
- access_level: open_access
  checksum: 5553c596bb4db0f38226a56bee9c87a1
  content_type: application/pdf
  creator: asandaue
  date_created: 2021-06-22T09:23:59Z
  date_updated: 2021-06-22T09:23:59Z
  file_id: '9584'
  file_name: 2020_CambridgeUniversityPress_Ferber.pdf
  file_size: 601516
  relation: main_file
  success: 1
file_date_updated: 2021-06-22T09:23:59Z
has_accepted_license: '1'
intvolume: '         8'
language:
- iso: eng
month: '11'
oa: 1
oa_version: Published Version
pmid: 1
publication: Forum of Mathematics
publication_identifier:
  eissn:
  - 2050-5094
publication_status: published
publisher: Cambridge University Press
quality_controlled: '1'
scopus_import: '1'
status: public
title: Almost all Steiner triple systems are almost resolvable
tmp:
  image: /images/cc_by.png
  legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
  name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
  short: CC BY (4.0)
type: journal_article
user_id: 0043cee0-e5fc-11ee-9736-f83bc23afbf0
volume: 8
year: '2020'
...
---
_id: '9630'
abstract:
- lang: eng
  text: Various kinds of data are routinely represented as discrete probability distributions.
    Examples include text documents summarized by histograms of word occurrences and
    images represented as histograms of oriented gradients. Viewing a discrete probability
    distribution as a point in the standard simplex of the appropriate dimension,
    we can understand collections of such objects in geometric and topological terms.  Importantly,
    instead of using the standard Euclidean distance, we look into dissimilarity measures
    with information-theoretic justification, and we develop the theory needed for
    applying topological data analysis in this setting. In doing so, we emphasize
    constructions that enable the usage of existing computational topology software
    in this context.
acknowledgement: This research is partially supported by the Office of Naval Research,
  through grant no. N62909-18-1-2038, and the DFG Collaborative Research Center TRR
  109, ‘Discretization in Geometry and Dynamics’, through grant no. I02979-N35 of
  the Austrian Science Fund (FWF).
article_processing_charge: Yes
article_type: original
author:
- first_name: Herbert
  full_name: Edelsbrunner, Herbert
  id: 3FB178DA-F248-11E8-B48F-1D18A9856A87
  last_name: Edelsbrunner
  orcid: 0000-0002-9823-6833
- first_name: Ziga
  full_name: Virk, Ziga
  id: 2E36B656-F248-11E8-B48F-1D18A9856A87
  last_name: Virk
- first_name: Hubert
  full_name: Wagner, Hubert
  id: 379CA8B8-F248-11E8-B48F-1D18A9856A87
  last_name: Wagner
  orcid: 0009-0009-9111-8429
citation:
  ama: Edelsbrunner H, Virk Z, Wagner H. Topological data analysis in information
    space. <i>Journal of Computational Geometry</i>. 2020;11(2):162-182. doi:<a href="https://doi.org/10.20382/jocg.v11i2a7">10.20382/jocg.v11i2a7</a>
  apa: Edelsbrunner, H., Virk, Z., &#38; Wagner, H. (2020). Topological data analysis
    in information space. <i>Journal of Computational Geometry</i>. Carleton University.
    <a href="https://doi.org/10.20382/jocg.v11i2a7">https://doi.org/10.20382/jocg.v11i2a7</a>
  chicago: Edelsbrunner, Herbert, Ziga Virk, and Hubert Wagner. “Topological Data
    Analysis in Information Space.” <i>Journal of Computational Geometry</i>. Carleton
    University, 2020. <a href="https://doi.org/10.20382/jocg.v11i2a7">https://doi.org/10.20382/jocg.v11i2a7</a>.
  ieee: H. Edelsbrunner, Z. Virk, and H. Wagner, “Topological data analysis in information
    space,” <i>Journal of Computational Geometry</i>, vol. 11, no. 2. Carleton University,
    pp. 162–182, 2020.
  ista: Edelsbrunner H, Virk Z, Wagner H. 2020. Topological data analysis in information
    space. Journal of Computational Geometry. 11(2), 162–182.
  mla: Edelsbrunner, Herbert, et al. “Topological Data Analysis in Information Space.”
    <i>Journal of Computational Geometry</i>, vol. 11, no. 2, Carleton University,
    2020, pp. 162–82, doi:<a href="https://doi.org/10.20382/jocg.v11i2a7">10.20382/jocg.v11i2a7</a>.
  short: H. Edelsbrunner, Z. Virk, H. Wagner, Journal of Computational Geometry 11
    (2020) 162–182.
corr_author: '1'
date_created: 2021-07-04T22:01:26Z
date_published: 2020-12-14T00:00:00Z
date_updated: 2026-04-02T14:35:31Z
day: '14'
ddc:
- '510'
- '000'
department:
- _id: HeEd
doi: 10.20382/jocg.v11i2a7
file:
- access_level: open_access
  checksum: f02d0b2b3838e7891a6c417fc34ffdcd
  content_type: application/pdf
  creator: asandaue
  date_created: 2021-08-11T11:55:11Z
  date_updated: 2021-08-11T11:55:11Z
  file_id: '9882'
  file_name: 2020_JournalOfComputationalGeometry_Edelsbrunner.pdf
  file_size: 1449234
  relation: main_file
  success: 1
file_date_updated: 2021-08-11T11:55:11Z
has_accepted_license: '1'
intvolume: '        11'
issue: '2'
language:
- iso: eng
license: https://creativecommons.org/licenses/by/3.0/
month: '12'
oa: 1
oa_version: Published Version
page: 162-182
project:
- _id: 0aa4bc98-070f-11eb-9043-e6fff9c6a316
  grant_number: I4887
  name: Persistent Homology, Algorithms and Stochastic Geometry
publication: Journal of Computational Geometry
publication_identifier:
  eissn:
  - 1920-180X
publication_status: published
publisher: Carleton University
quality_controlled: '1'
scopus_import: '1'
status: public
title: Topological data analysis in information space
tmp:
  image: /images/cc_by.png
  legal_code_url: https://creativecommons.org/licenses/by/3.0/legalcode
  name: Creative Commons Attribution 3.0 Unported (CC BY 3.0)
  short: CC BY (3.0)
type: journal_article
user_id: ba8df636-2132-11f1-aed0-ed93e2281fdd
volume: 11
year: '2020'
...
---
_id: '9631'
abstract:
- lang: eng
  text: The ability to leverage large-scale hardware parallelism has been one of the
    key enablers of the accelerated recent progress in machine learning. Consequently,
    there has been considerable effort invested into developing efficient parallel
    variants of classic machine learning algorithms. However, despite the wealth of
    knowledge on parallelization, some classic machine learning algorithms often prove
    hard to parallelize efficiently while maintaining convergence. In this paper,
    we focus on efficient parallel algorithms for the key machine learning task of
    inference on graphical models, in particular on the fundamental belief propagation
    algorithm. We address the challenge of efficiently parallelizing this classic
    paradigm by showing how to leverage scalable relaxed schedulers in this context.
    We present an extensive empirical study, showing that our approach outperforms
    previous parallel belief propagation implementations both in terms of scalability
    and in terms of wall-clock convergence time, on a range of practical applications.
acknowledgement: "We thank Marco Mondelli for discussions related to LDPC decoding,
  and Giorgi Nadiradze for discussions on analysis of relaxed schedulers. This project
  has received funding from the European Research Council (ERC) under the European\r\nUnion’s
  Horizon 2020 research and innovation programme (grant agreement No 805223 ScaleML)."
alternative_title:
- Advances in Neural Information Processing Systems
article_processing_charge: No
arxiv: 1
author:
- first_name: Vitaly
  full_name: Aksenov, Vitaly
  last_name: Aksenov
- first_name: Dan-Adrian
  full_name: Alistarh, Dan-Adrian
  id: 4A899BFC-F248-11E8-B48F-1D18A9856A87
  last_name: Alistarh
  orcid: 0000-0003-3650-940X
- first_name: Janne
  full_name: Korhonen, Janne
  id: C5402D42-15BC-11E9-A202-CA2BE6697425
  last_name: Korhonen
citation:
  ama: 'Aksenov V, Alistarh D-A, Korhonen J. Scalable belief propagation via relaxed
    scheduling. In: Vol 33. Neural Information Processing Systems Foundation; 2020:22361-22372.'
  apa: 'Aksenov, V., Alistarh, D.-A., &#38; Korhonen, J. (2020). Scalable belief propagation
    via relaxed scheduling (Vol. 33, pp. 22361–22372). Presented at the NeurIPS: Conference
    on Neural Information Processing Systems, Vancouver, Canada: Neural Information
    Processing Systems Foundation.'
  chicago: Aksenov, Vitaly, Dan-Adrian Alistarh, and Janne Korhonen. “Scalable Belief
    Propagation via Relaxed Scheduling,” 33:22361–72. Neural Information Processing
    Systems Foundation, 2020.
  ieee: 'V. Aksenov, D.-A. Alistarh, and J. Korhonen, “Scalable belief propagation
    via relaxed scheduling,” presented at the NeurIPS: Conference on Neural Information
    Processing Systems, Vancouver, Canada, 2020, vol. 33, pp. 22361–22372.'
  ista: 'Aksenov V, Alistarh D-A, Korhonen J. 2020. Scalable belief propagation via
    relaxed scheduling. NeurIPS: Conference on Neural Information Processing Systems,
    Advances in Neural Information Processing Systems, vol. 33, 22361–22372.'
  mla: Aksenov, Vitaly, et al. <i>Scalable Belief Propagation via Relaxed Scheduling</i>.
    Vol. 33, Neural Information Processing Systems Foundation, 2020, pp. 22361–72.
  short: V. Aksenov, D.-A. Alistarh, J. Korhonen, in:, Neural Information Processing
    Systems Foundation, 2020, pp. 22361–22372.
conference:
  end_date: 2020-12-12
  location: Vancouver, Canada
  name: 'NeurIPS: Conference on Neural Information Processing Systems'
  start_date: 2020-12-06
corr_author: '1'
date_created: 2021-07-04T22:01:26Z
date_published: 2020-12-06T00:00:00Z
date_updated: 2026-06-18T19:54:53Z
day: '06'
ddc:
- '000'
department:
- _id: DaAl
ec_funded: 1
external_id:
  arxiv:
  - '2002.11505'
intvolume: '        33'
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://proceedings.neurips.cc/paper/2020/hash/fdb2c3bab9d0701c4a050a4d8d782c7f-Abstract.html
month: '12'
oa: 1
oa_version: Published Version
page: 22361-22372
project:
- _id: 268A44D6-B435-11E9-9278-68D0E5697425
  call_identifier: H2020
  grant_number: '805223'
  name: Elastic Coordination for Scalable Machine Learning
publication_identifier:
  isbn:
  - '9781713829546'
  issn:
  - 1049-5258
publication_status: published
publisher: Neural Information Processing Systems Foundation
quality_controlled: '1'
scopus_import: '1'
status: public
title: Scalable belief propagation via relaxed scheduling
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 33
year: '2020'
...
---
_id: '9632'
abstract:
- lang: eng
  text: "Second-order information, in the form of Hessian- or Inverse-Hessian-vector
    products, is a fundamental tool for solving optimization problems. Recently, there
    has been significant interest in utilizing this information in the context of
    deep\r\nneural networks; however, relatively little is known about the quality
    of existing approximations in this context. Our work examines this question, identifies
    issues with existing approaches, and proposes a method called WoodFisher to compute
    a faithful and efficient estimate of the inverse Hessian. Our main application
    is to neural network compression, where we build on the classic Optimal Brain
    Damage/Surgeon framework. We demonstrate that WoodFisher significantly outperforms
    popular state-of-the-art methods for oneshot pruning. Further, even when iterative,
    gradual pruning is allowed, our method results in a gain in test accuracy over
    the state-of-the-art approaches, for standard image classification datasets such
    as ImageNet ILSVRC. We examine how our method can be extended to take into account
    first-order information, as well as\r\nillustrate its ability to automatically
    set layer-wise pruning thresholds and perform compression in the limited-data
    regime. The code is available at the following link, https://github.com/IST-DASLab/WoodFisher."
acknowledgement: This project has received funding from the European Research Council
  (ERC) under the European Union’s Horizon 2020 research and innovation programme
  (grant agreement No 805223 ScaleML). Also, we would like to thank Alexander Shevchenko,
  Alexandra Peste, and other members of the group for fruitful discussions.
alternative_title:
- Advances in Neural Information Processing Systems
article_processing_charge: No
arxiv: 1
author:
- first_name: Sidak Pal
  full_name: Singh, Sidak Pal
  id: DD138E24-D89D-11E9-9DC0-DEF6E5697425
  last_name: Singh
- first_name: Dan-Adrian
  full_name: Alistarh, Dan-Adrian
  id: 4A899BFC-F248-11E8-B48F-1D18A9856A87
  last_name: Alistarh
  orcid: 0000-0003-3650-940X
citation:
  ama: 'Singh SP, Alistarh D-A. WoodFisher: Efficient second-order approximation for
    neural network compression. In: Vol 33. Neural Information Processing Systems
    Foundation; 2020:18098-18109.'
  apa: 'Singh, S. P., &#38; Alistarh, D.-A. (2020). WoodFisher: Efficient second-order
    approximation for neural network compression (Vol. 33, pp. 18098–18109). Presented
    at the NeurIPS: Conference on Neural Information Processing Systems, Vancouver,
    Canada: Neural Information Processing Systems Foundation.'
  chicago: 'Singh, Sidak Pal, and Dan-Adrian Alistarh. “WoodFisher: Efficient Second-Order
    Approximation for Neural Network Compression,” 33:18098–109. Neural Information
    Processing Systems Foundation, 2020.'
  ieee: 'S. P. Singh and D.-A. Alistarh, “WoodFisher: Efficient second-order approximation
    for neural network compression,” presented at the NeurIPS: Conference on Neural
    Information Processing Systems, Vancouver, Canada, 2020, vol. 33, pp. 18098–18109.'
  ista: 'Singh SP, Alistarh D-A. 2020. WoodFisher: Efficient second-order approximation
    for neural network compression. NeurIPS: Conference on Neural Information Processing
    Systems, Advances in Neural Information Processing Systems, vol. 33, 18098–18109.'
  mla: 'Singh, Sidak Pal, and Dan-Adrian Alistarh. <i>WoodFisher: Efficient Second-Order
    Approximation for Neural Network Compression</i>. Vol. 33, Neural Information
    Processing Systems Foundation, 2020, pp. 18098–109.'
  short: S.P. Singh, D.-A. Alistarh, in:, Neural Information Processing Systems Foundation,
    2020, pp. 18098–18109.
conference:
  end_date: 2020-12-12
  location: Vancouver, Canada
  name: 'NeurIPS: Conference on Neural Information Processing Systems'
  start_date: 2020-12-06
corr_author: '1'
date_created: 2021-07-04T22:01:26Z
date_published: 2020-12-06T00:00:00Z
date_updated: 2026-06-18T19:55:12Z
day: '06'
ddc:
- '000'
department:
- _id: DaAl
- _id: ToHe
ec_funded: 1
external_id:
  arxiv:
  - '2004.14340'
intvolume: '        33'
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://proceedings.neurips.cc/paper/2020/hash/d1ff1ec86b62cd5f3903ff19c3a326b2-Abstract.html
month: '12'
oa: 1
oa_version: Published Version
page: 18098-18109
project:
- _id: 268A44D6-B435-11E9-9278-68D0E5697425
  call_identifier: H2020
  grant_number: '805223'
  name: Elastic Coordination for Scalable Machine Learning
publication_identifier:
  isbn:
  - '9781713829546'
  issn:
  - 1049-5258
publication_status: published
publisher: Neural Information Processing Systems Foundation
quality_controlled: '1'
scopus_import: '1'
status: public
title: 'WoodFisher: Efficient second-order approximation for neural network compression'
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 33
year: '2020'
...
---
_id: '9658'
abstract:
- lang: eng
  text: Macroscopic models of nucleation provide powerful tools for understanding
    activated phase transition processes. These models do not provide atomistic insights
    and can thus sometimes lack material-specific descriptions. Here, we provide a
    comprehensive framework for constructing a continuum picture from an atomistic
    simulation of homogeneous nucleation. We use this framework to determine the equilibrium
    shape of the solid nucleus that forms inside bulk liquid for a Lennard-Jones potential.
    From this shape, we then extract the anisotropy of the solid-liquid interfacial
    free energy, by performing a reverse Wulff construction in the space of spherical
    harmonic expansions. We find that the shape of the nucleus is nearly spherical
    and that its anisotropy can be perfectly described using classical models.
article_number: '044103'
article_processing_charge: No
article_type: original
arxiv: 1
author:
- first_name: Bingqing
  full_name: Cheng, Bingqing
  id: cbe3cda4-d82c-11eb-8dc7-8ff94289fcc9
  last_name: Cheng
  orcid: 0000-0002-3584-9632
- first_name: Michele
  full_name: Ceriotti, Michele
  last_name: Ceriotti
- first_name: Gareth A.
  full_name: Tribello, Gareth A.
  last_name: Tribello
citation:
  ama: Cheng B, Ceriotti M, Tribello GA. Classical nucleation theory predicts the
    shape of the nucleus in homogeneous solidification. <i>The Journal of Chemical
    Physics</i>. 2020;152(4). doi:<a href="https://doi.org/10.1063/1.5134461">10.1063/1.5134461</a>
  apa: Cheng, B., Ceriotti, M., &#38; Tribello, G. A. (2020). Classical nucleation
    theory predicts the shape of the nucleus in homogeneous solidification. <i>The
    Journal of Chemical Physics</i>. AIP Publishing. <a href="https://doi.org/10.1063/1.5134461">https://doi.org/10.1063/1.5134461</a>
  chicago: Cheng, Bingqing, Michele Ceriotti, and Gareth A. Tribello. “Classical Nucleation
    Theory Predicts the Shape of the Nucleus in Homogeneous Solidification.” <i>The
    Journal of Chemical Physics</i>. AIP Publishing, 2020. <a href="https://doi.org/10.1063/1.5134461">https://doi.org/10.1063/1.5134461</a>.
  ieee: B. Cheng, M. Ceriotti, and G. A. Tribello, “Classical nucleation theory predicts
    the shape of the nucleus in homogeneous solidification,” <i>The Journal of Chemical
    Physics</i>, vol. 152, no. 4. AIP Publishing, 2020.
  ista: Cheng B, Ceriotti M, Tribello GA. 2020. Classical nucleation theory predicts
    the shape of the nucleus in homogeneous solidification. The Journal of Chemical
    Physics. 152(4), 044103.
  mla: Cheng, Bingqing, et al. “Classical Nucleation Theory Predicts the Shape of
    the Nucleus in Homogeneous Solidification.” <i>The Journal of Chemical Physics</i>,
    vol. 152, no. 4, 044103, AIP Publishing, 2020, doi:<a href="https://doi.org/10.1063/1.5134461">10.1063/1.5134461</a>.
  short: B. Cheng, M. Ceriotti, G.A. Tribello, The Journal of Chemical Physics 152
    (2020).
date_created: 2021-07-15T07:22:24Z
date_published: 2020-01-31T00:00:00Z
date_updated: 2023-02-23T14:03:55Z
day: '31'
doi: 10.1063/1.5134461
extern: '1'
external_id:
  arxiv:
  - '1910.13481'
  pmid:
  - '32007057'
intvolume: '       152'
issue: '4'
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://pure.qub.ac.uk/en/publications/classical-nucleation-theory-predicts-the-shape-of-the-nucleus-in-homogeneous-solidification(56af848b-eee8-4e9b-93cf-667373e4a49b).html
month: '01'
oa: 1
oa_version: Submitted Version
pmid: 1
publication: The Journal of Chemical Physics
publication_identifier:
  eissn:
  - 1089-7690
  issn:
  - 0021-9606
publication_status: published
publisher: AIP Publishing
quality_controlled: '1'
scopus_import: '1'
status: public
title: Classical nucleation theory predicts the shape of the nucleus in homogeneous
  solidification
type: journal_article
user_id: 6785fbc1-c503-11eb-8a32-93094b40e1cf
volume: 152
year: '2020'
...
---
_id: '9664'
abstract:
- lang: eng
  text: Equilibrium molecular dynamics simulations, in combination with the Green-Kubo
    (GK) method, have been extensively used to compute the thermal conductivity of
    liquids. However, the GK method relies on an ambiguous definition of the microscopic
    heat flux, which depends on how one chooses to distribute energies over atoms.
    This ambiguity makes it problematic to employ the GK method for systems with nonpairwise
    interactions. In this work, we show that the hydrodynamic description of thermally
    driven density fluctuations can be used to obtain the thermal conductivity of
    a bulk fluid unambiguously, thereby bypassing the need to define the heat flux.
    We verify that, for a model fluid with only pairwise interactions, our method
    yields estimates of thermal conductivity consistent with the GK approach. We apply
    our approach to compute the thermal conductivity of a nonpairwise additive water
    model at supercritical conditions, and of a liquid hydrogen system described by
    a machine-learning interatomic potential, at 33 GPa and 2000 K.
article_number: '130602'
article_processing_charge: No
article_type: original
arxiv: 1
author:
- first_name: Bingqing
  full_name: Cheng, Bingqing
  id: cbe3cda4-d82c-11eb-8dc7-8ff94289fcc9
  last_name: Cheng
  orcid: 0000-0002-3584-9632
- first_name: Daan
  full_name: Frenkel, Daan
  last_name: Frenkel
citation:
  ama: Cheng B, Frenkel D. Computing the heat conductivity of fluids from density
    fluctuations. <i>Physical Review Letters</i>. 2020;125(13). doi:<a href="https://doi.org/10.1103/physrevlett.125.130602">10.1103/physrevlett.125.130602</a>
  apa: Cheng, B., &#38; Frenkel, D. (2020). Computing the heat conductivity of fluids
    from density fluctuations. <i>Physical Review Letters</i>. American Physical Society.
    <a href="https://doi.org/10.1103/physrevlett.125.130602">https://doi.org/10.1103/physrevlett.125.130602</a>
  chicago: Cheng, Bingqing, and Daan Frenkel. “Computing the Heat Conductivity of
    Fluids from Density Fluctuations.” <i>Physical Review Letters</i>. American Physical
    Society, 2020. <a href="https://doi.org/10.1103/physrevlett.125.130602">https://doi.org/10.1103/physrevlett.125.130602</a>.
  ieee: B. Cheng and D. Frenkel, “Computing the heat conductivity of fluids from density
    fluctuations,” <i>Physical Review Letters</i>, vol. 125, no. 13. American Physical
    Society, 2020.
  ista: Cheng B, Frenkel D. 2020. Computing the heat conductivity of fluids from density
    fluctuations. Physical Review Letters. 125(13), 130602.
  mla: Cheng, Bingqing, and Daan Frenkel. “Computing the Heat Conductivity of Fluids
    from Density Fluctuations.” <i>Physical Review Letters</i>, vol. 125, no. 13,
    130602, American Physical Society, 2020, doi:<a href="https://doi.org/10.1103/physrevlett.125.130602">10.1103/physrevlett.125.130602</a>.
  short: B. Cheng, D. Frenkel, Physical Review Letters 125 (2020).
date_created: 2021-07-15T12:15:14Z
date_published: 2020-09-25T00:00:00Z
date_updated: 2021-08-09T12:35:58Z
day: '25'
doi: 10.1103/physrevlett.125.130602
extern: '1'
external_id:
  arxiv:
  - '2005.07562'
  pmid:
  - '33034481'
intvolume: '       125'
issue: '13'
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://arxiv.org/abs/2005.07562
month: '09'
oa: 1
oa_version: Preprint
pmid: 1
publication: Physical Review Letters
publication_identifier:
  eissn:
  - 1079-7114
  issn:
  - 0031-9007
publication_status: published
publisher: American Physical Society
quality_controlled: '1'
scopus_import: '1'
status: public
title: Computing the heat conductivity of fluids from density fluctuations
type: journal_article
user_id: 6785fbc1-c503-11eb-8a32-93094b40e1cf
volume: 125
year: '2020'
...
---
OA_place: publisher
OA_type: hybrid
_id: '9666'
abstract:
- lang: eng
  text: Predicting phase stabilities of crystal polymorphs is central to computational
    materials science and chemistry. Such predictions are challenging because they
    first require searching for potential energy minima and then performing arduous
    free-energy calculations to account for entropic effects at finite temperatures.
    Here, we develop a framework that facilitates such predictions by exploiting all
    the information obtained from random searches of crystal structures. This framework
    combines automated clustering, classification and visualisation of crystal structures
    with machine-learning estimation of their enthalpy and entropy. We demonstrate
    the framework on the technologically important system of TiO2, which has many
    polymorphs, without relying on prior knowledge of known phases. We find a number
    of new phases and predict the phase diagram and metastabilities of crystal polymorphs
    at 1600 K, benchmarking the results against full free-energy calculations.
article_processing_charge: No
article_type: original
arxiv: 1
author:
- first_name: Aleks
  full_name: Reinhardt, Aleks
  last_name: Reinhardt
- first_name: Chris J.
  full_name: Pickard, Chris J.
  last_name: Pickard
- first_name: Bingqing
  full_name: Cheng, Bingqing
  id: cbe3cda4-d82c-11eb-8dc7-8ff94289fcc9
  last_name: Cheng
  orcid: 0000-0002-3584-9632
citation:
  ama: Reinhardt A, Pickard CJ, Cheng B. Predicting the phase diagram of titanium
    dioxide with random search and pattern recognition. <i>Physical Chemistry Chemical
    Physics</i>. 2020;22(22):12697-12705. doi:<a href="https://doi.org/10.1039/d0cp02513e">10.1039/d0cp02513e</a>
  apa: Reinhardt, A., Pickard, C. J., &#38; Cheng, B. (2020). Predicting the phase
    diagram of titanium dioxide with random search and pattern recognition. <i>Physical
    Chemistry Chemical Physics</i>. Royal Society of Chemistry. <a href="https://doi.org/10.1039/d0cp02513e">https://doi.org/10.1039/d0cp02513e</a>
  chicago: Reinhardt, Aleks, Chris J. Pickard, and Bingqing Cheng. “Predicting the
    Phase Diagram of Titanium Dioxide with Random Search and Pattern Recognition.”
    <i>Physical Chemistry Chemical Physics</i>. Royal Society of Chemistry, 2020.
    <a href="https://doi.org/10.1039/d0cp02513e">https://doi.org/10.1039/d0cp02513e</a>.
  ieee: A. Reinhardt, C. J. Pickard, and B. Cheng, “Predicting the phase diagram of
    titanium dioxide with random search and pattern recognition,” <i>Physical Chemistry
    Chemical Physics</i>, vol. 22, no. 22. Royal Society of Chemistry, pp. 12697–12705,
    2020.
  ista: Reinhardt A, Pickard CJ, Cheng B. 2020. Predicting the phase diagram of titanium
    dioxide with random search and pattern recognition. Physical Chemistry Chemical
    Physics. 22(22), 12697–12705.
  mla: Reinhardt, Aleks, et al. “Predicting the Phase Diagram of Titanium Dioxide
    with Random Search and Pattern Recognition.” <i>Physical Chemistry Chemical Physics</i>,
    vol. 22, no. 22, Royal Society of Chemistry, 2020, pp. 12697–705, doi:<a href="https://doi.org/10.1039/d0cp02513e">10.1039/d0cp02513e</a>.
  short: A. Reinhardt, C.J. Pickard, B. Cheng, Physical Chemistry Chemical Physics
    22 (2020) 12697–12705.
date_created: 2021-07-15T12:37:27Z
date_published: 2020-06-14T00:00:00Z
date_updated: 2024-10-16T12:29:54Z
day: '14'
ddc:
- '530'
doi: 10.1039/d0cp02513e
extern: '1'
external_id:
  arxiv:
  - '1909.08934'
  pmid:
  - '32459228'
file:
- access_level: open_access
  checksum: 0a6872972b1b2e60f9095d39b01753fa
  content_type: application/pdf
  creator: asandaue
  date_created: 2021-07-15T12:43:51Z
  date_updated: 2021-07-15T12:43:51Z
  file_id: '9667'
  file_name: 202_PhysicalChemistryChemicalPhysics_Reinhardt.pdf
  file_size: 3151206
  relation: main_file
  success: 1
file_date_updated: 2021-07-15T12:43:51Z
has_accepted_license: '1'
intvolume: '        22'
issue: '22'
language:
- iso: eng
month: '06'
oa: 1
oa_version: Published Version
page: 12697-12705
pmid: 1
publication: Physical Chemistry Chemical Physics
publication_identifier:
  eissn:
  - 1463-9084
  issn:
  - 1463-9076
publication_status: published
publisher: Royal Society of Chemistry
quality_controlled: '1'
scopus_import: '1'
status: public
title: Predicting the phase diagram of titanium dioxide with random search and pattern
  recognition
tmp:
  image: /images/cc_by.png
  legal_code_url: https://creativecommons.org/licenses/by/3.0/legalcode
  name: Creative Commons Attribution 3.0 Unported (CC BY 3.0)
  short: CC BY (3.0)
type: journal_article
user_id: 0043cee0-e5fc-11ee-9736-f83bc23afbf0
volume: 22
year: '2020'
...
---
_id: '9671'
abstract:
- lang: eng
  text: Water molecules can arrange into a liquid with complex hydrogen-bond networks
    and at least 17 experimentally confirmed ice phases with enormous structural diversity.
    It remains a puzzle how or whether this multitude of arrangements in different
    phases of water are related. Here we investigate the structural similarities between
    liquid water and a comprehensive set of 54 ice phases in simulations, by directly
    comparing their local environments using general atomic descriptors, and also
    by demonstrating that a machine-learning potential trained on liquid water alone
    can predict the densities, lattice energies, and vibrational properties of the
    ices. The finding that the local environments characterising the different ice
    phases are found in water sheds light on the phase behavior of water, and rationalizes
    the transferability of water models between different phases.
article_number: '5757'
article_processing_charge: No
article_type: original
author:
- first_name: Bartomeu
  full_name: Monserrat, Bartomeu
  last_name: Monserrat
- first_name: Jan Gerit
  full_name: Brandenburg, Jan Gerit
  last_name: Brandenburg
- first_name: Edgar A.
  full_name: Engel, Edgar A.
  last_name: Engel
- first_name: Bingqing
  full_name: Cheng, Bingqing
  id: cbe3cda4-d82c-11eb-8dc7-8ff94289fcc9
  last_name: Cheng
  orcid: 0000-0002-3584-9632
citation:
  ama: Monserrat B, Brandenburg JG, Engel EA, Cheng B. Liquid water contains the building
    blocks of diverse ice phases. <i>Nature Communications</i>. 2020;11(1). doi:<a
    href="https://doi.org/10.1038/s41467-020-19606-y">10.1038/s41467-020-19606-y</a>
  apa: Monserrat, B., Brandenburg, J. G., Engel, E. A., &#38; Cheng, B. (2020). Liquid
    water contains the building blocks of diverse ice phases. <i>Nature Communications</i>.
    Springer Nature. <a href="https://doi.org/10.1038/s41467-020-19606-y">https://doi.org/10.1038/s41467-020-19606-y</a>
  chicago: Monserrat, Bartomeu, Jan Gerit Brandenburg, Edgar A. Engel, and Bingqing
    Cheng. “Liquid Water Contains the Building Blocks of Diverse Ice Phases.” <i>Nature
    Communications</i>. Springer Nature, 2020. <a href="https://doi.org/10.1038/s41467-020-19606-y">https://doi.org/10.1038/s41467-020-19606-y</a>.
  ieee: B. Monserrat, J. G. Brandenburg, E. A. Engel, and B. Cheng, “Liquid water
    contains the building blocks of diverse ice phases,” <i>Nature Communications</i>,
    vol. 11, no. 1. Springer Nature, 2020.
  ista: Monserrat B, Brandenburg JG, Engel EA, Cheng B. 2020. Liquid water contains
    the building blocks of diverse ice phases. Nature Communications. 11(1), 5757.
  mla: Monserrat, Bartomeu, et al. “Liquid Water Contains the Building Blocks of Diverse
    Ice Phases.” <i>Nature Communications</i>, vol. 11, no. 1, 5757, Springer Nature,
    2020, doi:<a href="https://doi.org/10.1038/s41467-020-19606-y">10.1038/s41467-020-19606-y</a>.
  short: B. Monserrat, J.G. Brandenburg, E.A. Engel, B. Cheng, Nature Communications
    11 (2020).
date_created: 2021-07-15T14:01:35Z
date_published: 2020-11-13T00:00:00Z
date_updated: 2023-02-23T14:04:25Z
day: '13'
ddc:
- '530'
- '540'
doi: 10.1038/s41467-020-19606-y
extern: '1'
file:
- access_level: open_access
  checksum: 1edd9b6d8fa791f8094d87bd6453955b
  content_type: application/pdf
  creator: asandaue
  date_created: 2021-07-15T14:05:45Z
  date_updated: 2021-07-15T14:05:45Z
  file_id: '9672'
  file_name: 2020_NatureCommunications_Monserrat.pdf
  file_size: 1385954
  relation: main_file
  success: 1
file_date_updated: 2021-07-15T14:05:45Z
has_accepted_license: '1'
intvolume: '        11'
issue: '1'
language:
- iso: eng
month: '11'
oa: 1
oa_version: Published Version
publication: Nature Communications
publication_identifier:
  eissn:
  - 2041-1723
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
scopus_import: '1'
status: public
title: Liquid water contains the building blocks of diverse ice phases
tmp:
  image: /images/cc_by.png
  legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
  name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
  short: CC BY (4.0)
type: journal_article
user_id: 6785fbc1-c503-11eb-8a32-93094b40e1cf
volume: 11
year: '2020'
...
---
_id: '9675'
abstract:
- lang: eng
  text: The visualization of data is indispensable in scientific research, from the
    early stages when human insight forms to the final step of communicating results.
    In computational physics, chemistry and materials science, it can be as simple
    as making a scatter plot or as straightforward as looking through the snapshots
    of atomic positions manually. However, as a result of the "big data" revolution,
    these conventional approaches are often inadequate. The widespread adoption of
    high-throughput computation for materials discovery and the associated community-wide
    repositories have given rise to data sets that contain an enormous number of compounds
    and atomic configurations. A typical data set contains thousands to millions of
    atomic structures, along with a diverse range of properties such as formation
    energies, band gaps, or bioactivities.It would thus be desirable to have a data-driven
    and automated framework for visualizing and analyzing such structural data sets.
    The key idea is to construct a low-dimensional representation of the data, which
    facilitates navigation, reveals underlying patterns, and helps to identify data
    points with unusual attributes. Such data-intensive maps, often employing machine
    learning methods, are appearing more and more frequently in the literature. However,
    to the wider community, it is not always transparent how these maps are made and
    how they should be interpreted. Furthermore, while these maps undoubtedly serve
    a decorative purpose in academic publications, it is not always apparent what
    extra information can be garnered from reading or making them.This Account attempts
    to answer such questions. We start with a concise summary of the theory of representing
    chemical environments, followed by the introduction of a simple yet practical
    conceptual approach for generating structure maps in a generic and automated manner.
    Such analysis and mapping is made nearly effortless by employing the newly developed
    software tool ASAP. To showcase the applicability to a wide variety of systems
    in chemistry and materials science, we provide several illustrative examples,
    including crystalline and amorphous materials, interfaces, and organic molecules.
    In these examples, the maps not only help to sift through large data sets but
    also reveal hidden patterns that could be easily missed using conventional analyses.The
    explosion in the amount of computed information in chemistry and materials science
    has made visualization into a science in itself. Not only have we benefited from
    exploiting these visualization methods in previous works, we also believe that
    the automated mapping of data sets will in turn stimulate further creativity and
    exploration, as well as ultimately feed back into future advances in the respective
    fields.
article_processing_charge: No
article_type: original
author:
- first_name: Bingqing
  full_name: Cheng, Bingqing
  id: cbe3cda4-d82c-11eb-8dc7-8ff94289fcc9
  last_name: Cheng
  orcid: 0000-0002-3584-9632
- first_name: Ryan-Rhys
  full_name: Griffiths, Ryan-Rhys
  last_name: Griffiths
- first_name: Simon
  full_name: Wengert, Simon
  last_name: Wengert
- first_name: Christian
  full_name: Kunkel, Christian
  last_name: Kunkel
- first_name: Tamas
  full_name: Stenczel, Tamas
  last_name: Stenczel
- first_name: Bonan
  full_name: Zhu, Bonan
  last_name: Zhu
- first_name: Volker L.
  full_name: Deringer, Volker L.
  last_name: Deringer
- first_name: Noam
  full_name: Bernstein, Noam
  last_name: Bernstein
- first_name: Johannes T.
  full_name: Margraf, Johannes T.
  last_name: Margraf
- first_name: Karsten
  full_name: Reuter, Karsten
  last_name: Reuter
- first_name: Gabor
  full_name: Csanyi, Gabor
  last_name: Csanyi
citation:
  ama: Cheng B, Griffiths R-R, Wengert S, et al. Mapping materials and molecules.
    <i>Accounts of Chemical Research</i>. 2020;53(9):1981-1991. doi:<a href="https://doi.org/10.1021/acs.accounts.0c00403">10.1021/acs.accounts.0c00403</a>
  apa: Cheng, B., Griffiths, R.-R., Wengert, S., Kunkel, C., Stenczel, T., Zhu, B.,
    … Csanyi, G. (2020). Mapping materials and molecules. <i>Accounts of Chemical
    Research</i>. American Chemical Society. <a href="https://doi.org/10.1021/acs.accounts.0c00403">https://doi.org/10.1021/acs.accounts.0c00403</a>
  chicago: Cheng, Bingqing, Ryan-Rhys Griffiths, Simon Wengert, Christian Kunkel,
    Tamas Stenczel, Bonan Zhu, Volker L. Deringer, et al. “Mapping Materials and Molecules.”
    <i>Accounts of Chemical Research</i>. American Chemical Society, 2020. <a href="https://doi.org/10.1021/acs.accounts.0c00403">https://doi.org/10.1021/acs.accounts.0c00403</a>.
  ieee: B. Cheng <i>et al.</i>, “Mapping materials and molecules,” <i>Accounts of
    Chemical Research</i>, vol. 53, no. 9. American Chemical Society, pp. 1981–1991,
    2020.
  ista: Cheng B, Griffiths R-R, Wengert S, Kunkel C, Stenczel T, Zhu B, Deringer VL,
    Bernstein N, Margraf JT, Reuter K, Csanyi G. 2020. Mapping materials and molecules.
    Accounts of Chemical Research. 53(9), 1981–1991.
  mla: Cheng, Bingqing, et al. “Mapping Materials and Molecules.” <i>Accounts of Chemical
    Research</i>, vol. 53, no. 9, American Chemical Society, 2020, pp. 1981–91, doi:<a
    href="https://doi.org/10.1021/acs.accounts.0c00403">10.1021/acs.accounts.0c00403</a>.
  short: B. Cheng, R.-R. Griffiths, S. Wengert, C. Kunkel, T. Stenczel, B. Zhu, V.L.
    Deringer, N. Bernstein, J.T. Margraf, K. Reuter, G. Csanyi, Accounts of Chemical
    Research 53 (2020) 1981–1991.
date_created: 2021-07-16T06:25:53Z
date_published: 2020-08-14T00:00:00Z
date_updated: 2021-11-24T15:54:41Z
day: '14'
doi: 10.1021/acs.accounts.0c00403
extern: '1'
external_id:
  pmid:
  - '32794697'
intvolume: '        53'
issue: '9'
language:
- iso: eng
month: '08'
oa_version: None
page: 1981-1991
pmid: 1
publication: Accounts of Chemical Research
publication_identifier:
  eissn:
  - 1520-4898
  issn:
  - 0001-4842
publication_status: published
publisher: American Chemical Society
quality_controlled: '1'
scopus_import: '1'
status: public
title: Mapping materials and molecules
type: journal_article
user_id: 8b945eb4-e2f2-11eb-945a-df72226e66a9
volume: 53
year: '2020'
...
---
_id: '9685'
abstract:
- lang: eng
  text: Hydrogen, the simplest and most abundant element in the Universe, develops
    a remarkably complex behaviour upon compression^1. Since Wigner predicted the
    dissociation and metallization of solid hydrogen at megabar pressures almost a
    century ago^2, several efforts have been made to explain the many unusual properties
    of dense hydrogen, including a rich and poorly understood solid polymorphism^1,3-5,
    an anomalous melting line6 and the possible transition to a superconducting state^7.
    Experiments at such extreme conditions are challenging and often lead to hard-to-interpret
    and controversial observations, whereas theoretical investigations are constrained
    by the huge computational cost of sufficiently accurate quantum mechanical calculations.
    Here we present a theoretical study of the phase diagram of dense hydrogen that
    uses machine learning to 'learn' potential-energy surfaces and interatomic forces
    from reference calculations and then predict them at low computational cost, overcoming
    length- and timescale limitations. We reproduce both the re-entrant melting behaviour
    and the polymorphism of the solid phase. Simulations using our machine-learning-based
    potentials provide evidence for a continuous molecular-to-atomic transition in
    the liquid, with no first-order transition observed above the melting line. This
    suggests a smooth transition between insulating and metallic layers in giant gas
    planets, and reconciles existing discrepancies between experiments as a manifestation
    of supercritical behaviour.
article_processing_charge: No
article_type: original
arxiv: 1
author:
- first_name: Bingqing
  full_name: Cheng, Bingqing
  id: cbe3cda4-d82c-11eb-8dc7-8ff94289fcc9
  last_name: Cheng
  orcid: 0000-0002-3584-9632
- first_name: Guglielmo
  full_name: Mazzola, Guglielmo
  last_name: Mazzola
- first_name: Chris J.
  full_name: Pickard, Chris J.
  last_name: Pickard
- first_name: Michele
  full_name: Ceriotti, Michele
  last_name: Ceriotti
citation:
  ama: Cheng B, Mazzola G, Pickard CJ, Ceriotti M. Evidence for supercritical behaviour
    of high-pressure liquid hydrogen. <i>Nature</i>. 2020;585(7824):217-220. doi:<a
    href="https://doi.org/10.1038/s41586-020-2677-y">10.1038/s41586-020-2677-y</a>
  apa: Cheng, B., Mazzola, G., Pickard, C. J., &#38; Ceriotti, M. (2020). Evidence
    for supercritical behaviour of high-pressure liquid hydrogen. <i>Nature</i>. Springer
    Nature. <a href="https://doi.org/10.1038/s41586-020-2677-y">https://doi.org/10.1038/s41586-020-2677-y</a>
  chicago: Cheng, Bingqing, Guglielmo Mazzola, Chris J. Pickard, and Michele Ceriotti.
    “Evidence for Supercritical Behaviour of High-Pressure Liquid Hydrogen.” <i>Nature</i>.
    Springer Nature, 2020. <a href="https://doi.org/10.1038/s41586-020-2677-y">https://doi.org/10.1038/s41586-020-2677-y</a>.
  ieee: B. Cheng, G. Mazzola, C. J. Pickard, and M. Ceriotti, “Evidence for supercritical
    behaviour of high-pressure liquid hydrogen,” <i>Nature</i>, vol. 585, no. 7824.
    Springer Nature, pp. 217–220, 2020.
  ista: Cheng B, Mazzola G, Pickard CJ, Ceriotti M. 2020. Evidence for supercritical
    behaviour of high-pressure liquid hydrogen. Nature. 585(7824), 217–220.
  mla: Cheng, Bingqing, et al. “Evidence for Supercritical Behaviour of High-Pressure
    Liquid Hydrogen.” <i>Nature</i>, vol. 585, no. 7824, Springer Nature, 2020, pp.
    217–20, doi:<a href="https://doi.org/10.1038/s41586-020-2677-y">10.1038/s41586-020-2677-y</a>.
  short: B. Cheng, G. Mazzola, C.J. Pickard, M. Ceriotti, Nature 585 (2020) 217–220.
date_created: 2021-07-19T09:17:49Z
date_published: 2020-09-10T00:00:00Z
date_updated: 2021-08-09T12:38:01Z
day: '10'
doi: 10.1038/s41586-020-2677-y
extern: '1'
external_id:
  arxiv:
  - '1906.03341'
  pmid:
  - '32908269'
intvolume: '       585'
issue: '7824'
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://arxiv.org/abs/1906.03341
month: '09'
oa: 1
oa_version: Preprint
page: 217-220
pmid: 1
publication: Nature
publication_identifier:
  eissn:
  - 1476-4687
  issn:
  - 0028-0836
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
scopus_import: '1'
status: public
title: Evidence for supercritical behaviour of high-pressure liquid hydrogen
type: journal_article
user_id: 6785fbc1-c503-11eb-8a32-93094b40e1cf
volume: 585
year: '2020'
...
---
_id: '9699'
abstract:
- lang: eng
  text: "We investigate the structural similarities between liquid water and 53 ices,
    including 20 known crystalline phases. We base such similarity comparison on the
    local environments that consist of atoms within a certain cutoff radius of a central
    atom. We reveal that liquid water explores the local environments of the diverse
    ice phases, by directly comparing the environments in these phases using general
    atomic descriptors, and also by demonstrating that a machine-learning potential
    trained on liquid water alone can predict the densities, the lattice energies,
    and vibrational properties of the\r\nices. The finding that the local environments
    characterising the different ice phases are found in water sheds light on water
    phase behaviors, and rationalizes the transferability of water models between
    different phases."
article_number: '2006.13316'
article_processing_charge: No
arxiv: 1
author:
- first_name: Bartomeu
  full_name: Monserrat, Bartomeu
  last_name: Monserrat
- first_name: Jan Gerit
  full_name: Brandenburg, Jan Gerit
  last_name: Brandenburg
- first_name: Edgar A.
  full_name: Engel, Edgar A.
  last_name: Engel
- first_name: Bingqing
  full_name: Cheng, Bingqing
  id: cbe3cda4-d82c-11eb-8dc7-8ff94289fcc9
  last_name: Cheng
  orcid: 0000-0002-3584-9632
citation:
  ama: 'Monserrat B, Brandenburg JG, Engel EA, Cheng B. Extracting ice phases from
    liquid water: Why a machine-learning water model generalizes so well. <i>arXiv</i>.
    doi:<a href="https://doi.org/10.48550/arXiv.2006.13316">10.48550/arXiv.2006.13316</a>'
  apa: 'Monserrat, B., Brandenburg, J. G., Engel, E. A., &#38; Cheng, B. (n.d.). Extracting
    ice phases from liquid water: Why a machine-learning water model generalizes so
    well. <i>arXiv</i>. <a href="https://doi.org/10.48550/arXiv.2006.13316">https://doi.org/10.48550/arXiv.2006.13316</a>'
  chicago: 'Monserrat, Bartomeu, Jan Gerit Brandenburg, Edgar A. Engel, and Bingqing
    Cheng. “Extracting Ice Phases from Liquid Water: Why a Machine-Learning Water
    Model Generalizes so Well.” <i>ArXiv</i>, n.d. <a href="https://doi.org/10.48550/arXiv.2006.13316">https://doi.org/10.48550/arXiv.2006.13316</a>.'
  ieee: 'B. Monserrat, J. G. Brandenburg, E. A. Engel, and B. Cheng, “Extracting ice
    phases from liquid water: Why a machine-learning water model generalizes so well,”
    <i>arXiv</i>. .'
  ista: 'Monserrat B, Brandenburg JG, Engel EA, Cheng B. Extracting ice phases from
    liquid water: Why a machine-learning water model generalizes so well. arXiv, 2006.13316.'
  mla: 'Monserrat, Bartomeu, et al. “Extracting Ice Phases from Liquid Water: Why
    a Machine-Learning Water Model Generalizes so Well.” <i>ArXiv</i>, 2006.13316,
    doi:<a href="https://doi.org/10.48550/arXiv.2006.13316">10.48550/arXiv.2006.13316</a>.'
  short: B. Monserrat, J.G. Brandenburg, E.A. Engel, B. Cheng, ArXiv (n.d.).
date_created: 2021-07-20T11:25:15Z
date_published: 2020-06-23T00:00:00Z
date_updated: 2024-10-14T12:05:56Z
day: '23'
doi: 10.48550/arXiv.2006.13316
extern: '1'
external_id:
  arxiv:
  - '2006.13316'
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://arxiv.org/abs/2006.13316
month: '06'
oa: 1
oa_version: Submitted Version
publication: arXiv
publication_status: submitted
status: public
title: 'Extracting ice phases from liquid water: Why a machine-learning water model
  generalizes so well'
type: preprint
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2020'
...
---
_id: '9706'
abstract:
- lang: eng
  text: 'Additional file 2: Supplementary Tables. The association of pre-adjusted
    protein levels with biological and technical covariates. Protein levels were adjusted
    for age, sex, array plate and four genetic principal components (population structure)
    prior to analyses. Significant associations are emboldened. (Table S1). pQTLs
    associated with inflammatory biomarker levels from Bayesian penalised regression
    model (Posterior Inclusion Probability > 95%). (Table S2). All pQTLs associated
    with inflammatory biomarker levels from ordinary least squares regression model
    (P < 7.14 × 10− 10). (Table S3). Summary of lambda values relating to ordinary
    least squares GWAS and EWAS performed on inflammatory protein levels (n = 70)
    in Lothian Birth Cohort 1936 study. (Table S4). Conditionally significant pQTLs
    associated with inflammatory biomarker levels from ordinary least squares regression
    model (P < 7.14 × 10− 10). (Table S5). Comparison of variance explained by ordinary
    least squares and Bayesian penalised regression models for concordantly identified
    SNPs. (Table S6). Estimate of heritability for blood protein levels as well as
    proportion of variance explained attributable to different prior mixtures. (Table
    S7). Comparison of heritability estimates from Ahsan et al. (maximum likelihood)
    and Hillary et al. (Bayesian penalised regression). (Table S8). List of concordant
    SNPs identified by linear model and Bayesian penalised regression and whether
    they have been previously identified as eQTLs. (Table S9). Bayesian tests of colocalisation
    for cis pQTLs and cis eQTLs. (Table S10). Sherlock algorithm: Genes whose expression
    are putatively associated with circulating inflammatory proteins that harbour
    pQTLs. (Table S11). CpGs associated with inflammatory protein biomarkers as identified
    by Bayesian model (Bayesian model; Posterior Inclusion Probability > 95%). (Table
    S12). CpGs associated with inflammatory protein biomarkers as identified by linear
    model (limma) at P < 5.14 × 10− 10. (Table S13). CpGs associated with inflammatory
    protein biomarkers as identified by mixed linear model (OSCA) at P < 5.14 × 10− 10.
    (Table S14). Estimate of variance explained for blood protein levels by DNA methylation
    as well as proportion of explained attributable to different prior mixtures -
    BayesR+. (Table S15). Comparison of variance in protein levels explained by genome-wide
    DNA methylation data by mixed linear model (OSCA) and Bayesian penalised regression
    model (BayesR+). (Table S16). Variance in circulating inflammatory protein biomarker
    levels explained by common genetic and methylation data (joint and conditional
    estimates from BayesR+). Ordered by combined variance explained by genetic and
    epigenetic data - smallest to largest. Significant results from t-tests comparing
    distributions for variance explained by methylation or genetics alone versus combined
    estimate are emboldened. (Table S17). Genetic and epigenetic factors identified
    by BayesR+ when conditioning on all SNPs and CpGs together. (Table S18). Mendelian
    Randomisation analyses to assess whether proteins with concordantly identified
    genetic signals are causally associated with Alzheimer’s disease risk. (Table
    S19).'
article_processing_charge: No
author:
- first_name: Robert F.
  full_name: Hillary, Robert F.
  last_name: Hillary
- first_name: Daniel
  full_name: Trejo-Banos, Daniel
  last_name: Trejo-Banos
- first_name: Athanasios
  full_name: Kousathanas, Athanasios
  last_name: Kousathanas
- first_name: Daniel L.
  full_name: McCartney, Daniel L.
  last_name: McCartney
- first_name: Sarah E.
  full_name: Harris, Sarah E.
  last_name: Harris
- first_name: Anna J.
  full_name: Stevenson, Anna J.
  last_name: Stevenson
- first_name: Marion
  full_name: Patxot, Marion
  last_name: Patxot
- first_name: Sven Erik
  full_name: Ojavee, Sven Erik
  last_name: Ojavee
- first_name: Qian
  full_name: Zhang, Qian
  last_name: Zhang
- first_name: David C.
  full_name: Liewald, David C.
  last_name: Liewald
- first_name: Craig W.
  full_name: Ritchie, Craig W.
  last_name: Ritchie
- first_name: Kathryn L.
  full_name: Evans, Kathryn L.
  last_name: Evans
- first_name: Elliot M.
  full_name: Tucker-Drob, Elliot M.
  last_name: Tucker-Drob
- first_name: Naomi R.
  full_name: Wray, Naomi R.
  last_name: Wray
- first_name: 'Allan F. '
  full_name: 'McRae, Allan F. '
  last_name: McRae
- first_name: Peter M.
  full_name: Visscher, Peter M.
  last_name: Visscher
- first_name: Ian J.
  full_name: Deary, Ian J.
  last_name: Deary
- first_name: Matthew Richard
  full_name: Robinson, Matthew Richard
  id: E5D42276-F5DA-11E9-8E24-6303E6697425
  last_name: Robinson
  orcid: 0000-0001-8982-8813
- first_name: 'Riccardo E. '
  full_name: 'Marioni, Riccardo E. '
  last_name: Marioni
citation:
  ama: Hillary RF, Trejo-Banos D, Kousathanas A, et al. Additional file 2 of multi-method
    genome- and epigenome-wide studies of inflammatory protein levels in healthy older
    adults. 2020. doi:<a href="https://doi.org/10.6084/m9.figshare.12629697.v1">10.6084/m9.figshare.12629697.v1</a>
  apa: Hillary, R. F., Trejo-Banos, D., Kousathanas, A., McCartney, D. L., Harris,
    S. E., Stevenson, A. J., … Marioni, R. E. (2020). Additional file 2 of multi-method
    genome- and epigenome-wide studies of inflammatory protein levels in healthy older
    adults. Springer Nature. <a href="https://doi.org/10.6084/m9.figshare.12629697.v1">https://doi.org/10.6084/m9.figshare.12629697.v1</a>
  chicago: Hillary, Robert F., Daniel Trejo-Banos, Athanasios Kousathanas, Daniel
    L. McCartney, Sarah E. Harris, Anna J. Stevenson, Marion Patxot, et al. “Additional
    File 2 of Multi-Method Genome- and Epigenome-Wide Studies of Inflammatory Protein
    Levels in Healthy Older Adults.” Springer Nature, 2020. <a href="https://doi.org/10.6084/m9.figshare.12629697.v1">https://doi.org/10.6084/m9.figshare.12629697.v1</a>.
  ieee: R. F. Hillary <i>et al.</i>, “Additional file 2 of multi-method genome- and
    epigenome-wide studies of inflammatory protein levels in healthy older adults.”
    Springer Nature, 2020.
  ista: Hillary RF, Trejo-Banos D, Kousathanas A, McCartney DL, Harris SE, Stevenson
    AJ, Patxot M, Ojavee SE, Zhang Q, Liewald DC, Ritchie CW, Evans KL, Tucker-Drob
    EM, Wray NR, McRae AF, Visscher PM, Deary IJ, Robinson MR, Marioni RE. 2020. Additional
    file 2 of multi-method genome- and epigenome-wide studies of inflammatory protein
    levels in healthy older adults, Springer Nature, <a href="https://doi.org/10.6084/m9.figshare.12629697.v1">10.6084/m9.figshare.12629697.v1</a>.
  mla: Hillary, Robert F., et al. <i>Additional File 2 of Multi-Method Genome- and
    Epigenome-Wide Studies of Inflammatory Protein Levels in Healthy Older Adults</i>.
    Springer Nature, 2020, doi:<a href="https://doi.org/10.6084/m9.figshare.12629697.v1">10.6084/m9.figshare.12629697.v1</a>.
  short: R.F. Hillary, D. Trejo-Banos, A. Kousathanas, D.L. McCartney, S.E. Harris,
    A.J. Stevenson, M. Patxot, S.E. Ojavee, Q. Zhang, D.C. Liewald, C.W. Ritchie,
    K.L. Evans, E.M. Tucker-Drob, N.R. Wray, A.F. McRae, P.M. Visscher, I.J. Deary,
    M.R. Robinson, R.E. Marioni, (2020).
date_created: 2021-07-23T08:59:15Z
date_published: 2020-07-09T00:00:00Z
date_updated: 2026-04-02T14:28:32Z
day: '09'
department:
- _id: MaRo
doi: 10.6084/m9.figshare.12629697.v1
has_accepted_license: '1'
main_file_link:
- open_access: '1'
  url: https://doi.org/10.6084/m9.figshare.12629697.v1
month: '07'
oa: 1
oa_version: Published Version
other_data_license: CC0 + CC BY (4.0)
publisher: Springer Nature
related_material:
  record:
  - id: '8133'
    relation: used_in_publication
    status: public
status: public
title: Additional file 2 of multi-method genome- and epigenome-wide studies of inflammatory
  protein levels in healthy older adults
tmp:
  image: /images/cc_by.png
  legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
  name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
  short: CC BY (4.0)
type: research_data_reference
user_id: 6785fbc1-c503-11eb-8a32-93094b40e1cf
year: '2020'
...
---
_id: '9708'
abstract:
- lang: eng
  text: This research data supports 'Hard antinodal gap revealed by quantum oscillations
    in the pseudogap regime of underdoped high-Tc superconductors'. A Readme file
    for plotting each figure is provided.
article_processing_charge: No
author:
- first_name: Mate
  full_name: Hartstein, Mate
  last_name: Hartstein
- first_name: Yu-Te
  full_name: Hsu, Yu-Te
  last_name: Hsu
- first_name: Kimberly A
  full_name: Modic, Kimberly A
  id: 13C26AC0-EB69-11E9-87C6-5F3BE6697425
  last_name: Modic
  orcid: 0000-0001-9760-3147
- first_name: Juan
  full_name: Porras, Juan
  last_name: Porras
- first_name: Toshinao
  full_name: Loew, Toshinao
  last_name: Loew
- first_name: Matthieu
  full_name: Le Tacon, Matthieu
  last_name: Le Tacon
- first_name: Huakun
  full_name: Zuo, Huakun
  last_name: Zuo
- first_name: Jinhua
  full_name: Wang, Jinhua
  last_name: Wang
- first_name: Zengwei
  full_name: Zhu, Zengwei
  last_name: Zhu
- first_name: Mun
  full_name: Chan, Mun
  last_name: Chan
- first_name: Ross
  full_name: McDonald, Ross
  last_name: McDonald
- first_name: Gilbert
  full_name: Lonzarich, Gilbert
  last_name: Lonzarich
- first_name: Bernhard
  full_name: Keimer, Bernhard
  last_name: Keimer
- first_name: Suchitra
  full_name: Sebastian, Suchitra
  last_name: Sebastian
- first_name: Neil
  full_name: Harrison, Neil
  last_name: Harrison
citation:
  ama: Hartstein M, Hsu Y-T, Modic KA, et al. Accompanying dataset for “Hard antinodal
    gap revealed by quantum oscillations in the pseudogap regime of underdoped high-Tc
    superconductors.” 2020. doi:<a href="https://doi.org/10.17863/cam.50169">10.17863/cam.50169</a>
  apa: Hartstein, M., Hsu, Y.-T., Modic, K. A., Porras, J., Loew, T., Le Tacon, M.,
    … Harrison, N. (2020). Accompanying dataset for “Hard antinodal gap revealed by
    quantum oscillations in the pseudogap regime of underdoped high-Tc superconductors.”
    Apollo - University of Cambridge. <a href="https://doi.org/10.17863/cam.50169">https://doi.org/10.17863/cam.50169</a>
  chicago: Hartstein, Mate, Yu-Te Hsu, Kimberly A Modic, Juan Porras, Toshinao Loew,
    Matthieu Le Tacon, Huakun Zuo, et al. “Accompanying Dataset for ‘Hard Antinodal
    Gap Revealed by Quantum Oscillations in the Pseudogap Regime of Underdoped High-Tc
    Superconductors.’” Apollo - University of Cambridge, 2020. <a href="https://doi.org/10.17863/cam.50169">https://doi.org/10.17863/cam.50169</a>.
  ieee: M. Hartstein <i>et al.</i>, “Accompanying dataset for ‘Hard antinodal gap
    revealed by quantum oscillations in the pseudogap regime of underdoped high-Tc
    superconductors.’” Apollo - University of Cambridge, 2020.
  ista: Hartstein M, Hsu Y-T, Modic KA, Porras J, Loew T, Le Tacon M, Zuo H, Wang
    J, Zhu Z, Chan M, McDonald R, Lonzarich G, Keimer B, Sebastian S, Harrison N.
    2020. Accompanying dataset for ‘Hard antinodal gap revealed by quantum oscillations
    in the pseudogap regime of underdoped high-Tc superconductors’, Apollo - University
    of Cambridge, <a href="https://doi.org/10.17863/cam.50169">10.17863/cam.50169</a>.
  mla: Hartstein, Mate, et al. <i>Accompanying Dataset for “Hard Antinodal Gap Revealed
    by Quantum Oscillations in the Pseudogap Regime of Underdoped High-Tc Superconductors.”</i>
    Apollo - University of Cambridge, 2020, doi:<a href="https://doi.org/10.17863/cam.50169">10.17863/cam.50169</a>.
  short: M. Hartstein, Y.-T. Hsu, K.A. Modic, J. Porras, T. Loew, M. Le Tacon, H.
    Zuo, J. Wang, Z. Zhu, M. Chan, R. McDonald, G. Lonzarich, B. Keimer, S. Sebastian,
    N. Harrison, (2020).
date_created: 2021-07-23T10:00:35Z
date_published: 2020-05-29T00:00:00Z
date_updated: 2025-07-10T11:54:51Z
day: '29'
department:
- _id: KiMo
doi: 10.17863/cam.50169
has_accepted_license: '1'
main_file_link:
- open_access: '1'
  url: https://doi.org/10.17863/CAM.50169
month: '05'
oa: 1
oa_version: Published Version
publisher: Apollo - University of Cambridge
related_material:
  record:
  - id: '7942'
    relation: used_in_publication
    status: public
status: public
title: Accompanying dataset for 'Hard antinodal gap revealed by quantum oscillations
  in the pseudogap regime of underdoped high-Tc superconductors'
tmp:
  image: /images/cc_by.png
  legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
  name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
  short: CC BY (4.0)
type: research_data_reference
user_id: 6785fbc1-c503-11eb-8a32-93094b40e1cf
year: '2020'
...
