M. Hledik, “Genetic information and biological optimization,” Institute of Science and Technology Austria, 2024.

A. Agresti and M. Veraar, “Stochastic maximal Lp(Lq)-regularity for second order systems with periodic boundary conditions,” Annales de l’institut Henri Poincare Probability and Statistics, vol. 60, no. 1. Institute of Mathematical Statistics, pp. 413–430, 2024.

C. Chintaluri et al., “kCSD-python, reliable current source density estimation with quality control,” PLoS Computational Biology, vol. 20, no. 3. Public Library of Science, 2024.

B. Zens et al., “Lift-out cryo-FIBSEM and cryo-ET reveal the ultrastructural landscape of extracellular matrix,” Journal of Cell Biology, vol. 223, no. 6. Rockefeller University Press, 2024.

D. Brückner and C. P. Broedersz, “Learning dynamical models of single and collective cell migration: a review,” Reports on Progress in Physics, vol. 87, no. 5. IOP Publishing, 2024.

L. Viljakainen et al., “Antiviral immune response reveals host-specific virus infections in natural ant populations,” Frontiers in Microbiology, vol. 14. Frontiers, 2023.

A. Mrestani, K. Lichter, A. L. Sirén, M. Heckmann, M. M. Paul, and M. Pauli, “Single-molecule localization microscopy of presynaptic active zones in Drosophila melanogaster after rapid cryofixation,” International Journal of Molecular Sciences, vol. 24, no. 3. MDPI, 2023.

M. Lechner, A. Amini, D. Rus, and T. A. Henzinger, “Revisiting the adversarial robustness-accuracy tradeoff in robot learning,” IEEE Robotics and Automation Letters, vol. 8, no. 3. Institute of Electrical and Electronics Engineers, pp. 1595–1602, 2023.

J. S. Rothman, C. Borges Merjane, N. Holderith, P. M. Jonas, and R. Angus Silver, “Validation of a stereological method for estimating particle size and density from 2D projections with high accuracy,” PLoS ONE, vol. 18, no. 3 March. Public Library of Science, 2023.

M. A. Pak et al., “Using AlphaFold to predict the impact of single mutations on protein stability and function,” PLoS ONE, vol. 18, no. 3. Public Library of Science, 2023.

T. Brandstätter, D. Brückner, Y. L. Han, R. Alert, M. Guo, and C. P. Broedersz, “Curvature induces active velocity waves in rotating spherical tissues,” Nature Communications, vol. 14. Springer Nature, 2023.

N. Benes, L. Brim, O. Huvar, S. Pastva, and D. Safránek, “Boolean network sketches: A unifying framework for logical model inference,” Bioinformatics, vol. 39, no. 4. Oxford Academic, 2023.

A. Zavadakova, L. Vistejnova, T. Belinova, F. Tichanek, D. Bilikova, and P. R. Mouton, “Novel stereological method for estimation of cell counts in 3D collagen scaffolds,” Scientific Reports, vol. 13, no. 1. Springer Nature, 2023.

D. Shipilina, A. Pal, S. Stankowski, Y. F. Chan, and N. H. Barton, “On the origin and structure of haplotype blocks,” Molecular Ecology, vol. 32, no. 6. Wiley, pp. 1441–1457, 2023.

P. Koehl, A. Akopyan, and H. Edelsbrunner, “Computing the volume, surface area, mean, and Gaussian curvatures of molecules and their derivatives,” Journal of Chemical Information and Modeling, vol. 63, no. 3. American Chemical Society, pp. 973–985, 2023.

F. Lombardi, S. Pepic, O. Shriki, G. Tkadik, and D. De Martino, “Statistical modeling of adaptive neural networks explains co-existence of avalanches and oscillations in resting human brain,” Nature Computational Science, vol. 3. Springer Nature, pp. 254–263, 2023.

K. Tojo, A. Shamir, B. Bickel, and N. Umetani, “Stealth shaper: Reflectivity optimization as surface stylization,” in SIGGRAPH 2023 Conference Proceedings, Los Angeles, CA, United States, 2023.

T. A. Henzinger, M. Karimi, K. Kueffner, and K. Mallik, “Monitoring algorithmic fairness,” in Computer Aided Verification, Paris, France, 2023, vol. 13965, pp. 358–382.

S. Sinha, P. Gehler, F. Locatello, and B. Schiele, “TeST: Test-time Self-Training under distribution shift,” in 2023 IEEE/CVF Winter Conference on Applications of Computer Vision, Waikoloa, HI, United States, 2023.

F. Montagna, N. Noceti, L. Rosasco, K. Zhang, and F. Locatello, “Causal discovery with score matching on additive models with arbitrary noise,” in 2nd Conference on Causal Learning and Reasoning, Tübingen, Germany, 2023.

L. Erdös and Y. Xu, “Small deviation estimates for the largest eigenvalue of Wigner matrices,” Bernoulli, vol. 29, no. 2. Bernoulli Society for Mathematical Statistics and Probability, pp. 1063–1079, 2023.

J. D. Boissonnat and M. Wintraecken, “The reach of subsets of manifolds,” Journal of Applied and Computational Topology, vol. 7. Springer Nature, pp. 619–641, 2023.

D. Balazs and M. Ibáñez, “Widening the use of 3D printing,” Science, vol. 381, no. 6665. AAAS, pp. 1413–1414, 2023.

J. Barbier, F. Camilli, M. Mondelli, and M. Sáenz, “Fundamental limits in structured principal component analysis and how to reach them,” Proceedings of the National Academy of Sciences of the United States of America, vol. 120, no. 30. National Academy of Sciences, 2023.

G. Cipolloni, L. Erdös, and D. J. Schröder, “Functional central limit theorems for Wigner matrices,” Annals of Applied Probability, vol. 33, no. 1. Institute of Mathematical Statistics, pp. 447–489, 2023.

B. J. Confavreux, “Synapseek: Meta-learning synaptic plasticity rules,” Institute of Science and Technology Austria, 2023.

E. Frantar and D.-A. Alistarh, “SparseGPT: Massive language models can be accurately pruned in one-shot,” in Proceedings of the 40th International Conference on Machine Learning, Honolulu, Hawaii, HI, United States, 2023, vol. 202, pp. 10323–10337.

V. Kolmogorov, “Solving relaxations of MAP-MRF problems: Combinatorial in-face Frank-Wolfe directions,” in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Vancouver, Canada, 2023, vol. 2023, pp. 11980–11989.

P. Rao et al., “A deeper analysis of volumetric relightiable faces,” International Journal of Computer Vision. Springer Nature, 2023.

M. Zemlicka et al., “Compact vacuum-gap transmon qubits: Selective and sensitive probes for superconductor surface losses,” Physical Review Applied, vol. 20, no. 4. American Physical Society, 2023.

R. Kaiyrzhanov et al., “Bi-allelic ACB variants lead to a neurodevelopmental syndrome with progressive and complex movement disorders,” Brain. Oxford University Press, 2023.

L. Erdös and H. C. Ji, “Functional CLT for non-Hermitian random matrices,” Annales de l’institut Henri Poincare (B) Probability and Statistics, vol. 59, no. 4. Institute of Mathematical Statistics, pp. 2083–2105, 2023.

K. Liao, T. Tricard, M. Piovarci, H.-P. Seidel, and V. Babaei, “Learning deposition policies for fused multi-material 3D printing,” in 2023 IEEE International Conference on Robotics and Automation, London, United Kingdom, 2023, vol. 2023, pp. 12345–12352.

Y. Xu, T. Q. Hou, S. S. Liang, and M. Mondelli, “Approximate message passing for multi-layer estimation in rotationally invariant models,” in 2023 IEEE Information Theory Workshop, Saint-Malo, France, 2023, pp. 294–298.

F. Zhong, Y. Xu, H. Zhao, and L. Lu, “As-Continuous-As-Possible extrusion-based fabrication of surface models,” ACM Transactions on Graphics, vol. 42, no. 3. Association for Computing Machinery, 2023.

E. Méhes et al., “D cell segregation geometry and dynamics are governed by tissue surface tension regulation,” Communications Biology, vol. 6. Springer Nature, 2023.

S. J. Henheik and R. Tumulka, “Creation rate of Dirac particles at a point source,” Journal of Physics A: Mathematical and Theoretical, vol. 56, no. 44. IOP Publishing, 2023.

R. He et al., “A 3d4d5d high entropy alloy as a bifunctional oxygen catalyst for robust aqueous zinc–air batteries,” Advanced Materials. Wiley, 2023.

Á. Ambrus, M. Csikós, G. Kiss, J. Pach, and G. Somlai, “Optimal embedded and enclosing isosceles triangles,” International Journal of Foundations of Computer Science, vol. 34, no. 7. World Scientific Publishing, pp. 737–760, 2023.

B. Auerbach, M. Cueto Noval, G. Pascual Perez, and K. Z. Pietrzak, “On the cost of post-compromise security in concurrent Continuous Group-Key Agreement,” in 21st International Conference on Theory of Cryptography, Taipei, Taiwan, 2023, vol. 14371, pp. 271–300.

X. Ding and H. C. Ji, “Local laws for multiplication of random matrices,” The Annals of Applied Probability, vol. 33, no. 4. Institute of Mathematical Statistics, pp. 2981–3009, 2023.

J. G. Danzl, “Research data for the publication ‘Dense 4D nanoscale reconstruction of living brain tissue.’” Institute of Science and Technology Austria, 2023.

P. Velicky et al., “Dense 4D nanoscale reconstruction of living brain tissue,” Nature Methods, vol. 20. Springer Nature, pp. 1256–1265, 2023.

J. G. Danzl and P. Velicky, “LIONESS enables 4D nanoscale reconstruction of living brain tissue,” Nature Methods, vol. 20, no. 8. Springer Nature, pp. 1141–1142, 2023.

K. Schnelli and Y. Xu, “Convergence rate to the Tracy–Widom laws for the largest eigenvalue of sample covariance matrices,” The Annals of Applied Probability, vol. 33, no. 1. Institute of Mathematical Statistics, pp. 677–725, 2023.

V. Cohen-Addad, D. Saulpic, and C. Schwiegelshohn, “Deterministic clustering in high dimensional spaces: Sketches and approximation,” in 2023 IEEE 64th Annual Symposium on Foundations of Computer Science, Santa Cruz, CA, United States, 2023, pp. 1105–1130.

M. Mund et al., “Clathrin coats partially preassemble and subsequently bend during endocytosis,” Journal of Cell Biology, vol. 222, no. 3. Rockefeller University Press, 2023.

B. Chen et al., “The effect of display capabilities on the gloss consistency between real and virtual objects,” in Proceedings of the SIGGRAPH Asia 2023 Conference, Sydney, Australia, 2023.

M. Freire, M. Bhargava, C. Schreck, P.-A. Hugron, B. Bickel, and S. Lefebvre, “PCBend: Light up your 3D shapes with foldable circuit boards,” Transactions on Graphics, vol. 42, no. 4. Association for Computing Machinery, 2023.

A. Franschitz, “Individual and social immunity against viral infections in ants,” Institute of Science and Technology Austria, 2023.

J. Condor, M. Piovarci, B. Bickel, and P. Didyk, “Gloss-aware color correction for 3D printing,” in SIGGRAPH ’23 Conference Proceedings, Los Angeles, CA, United States, 2023.

B. Zens, “Ultrastructural characterization of natively preserved extracellular matrix by cryo-electron tomography,” Institute of Science and Technology Austria, 2023.

C. Hafner, “Inverse shape design with parametric representations: Kirchhoff Rods and parametric surface models,” Institute of Science and Technology Austria, 2023.

A. Davidovi, R. P. Chait, G. Batt, and J. Ruess, “Parameter inference for stochastic biochemical models from perturbation experiments parallelised at the single cell level,” PLoS Computational Biology, vol. 18, no. 3. Public Library of Science, 2022.

V. Ngampruetikorn, V. Sachdeva, J. Torrence, J. Humplik, D. J. Schwab, and S. E. Palmer, “Inferring couplings in networks across order-disorder phase transitions,” Physical Review Research, vol. 4, no. 2. American Physical Society, 2022.

B. Chen et al., “Gloss management for consistent reproduction of real and virtual objects,” in SIGGRAPH Asia 2022 Conference Papers, Daegu, South Korea, 2022, vol. 2022.

J. Barbier, T. Hou, M. Mondelli, and M. Saenz, “The price of ignorance: How much does it cost to forget noise structure in low-rank matrix estimation?,” arXiv. .

M. Kneib et al., “Sub-seasonal variability of supraglacial ice cliff melt rates and associated processes from time-lapse photogrammetry,” The Cryosphere, vol. 16, no. 11. Copernicus Publications, pp. 4701–4725, 2022.

T. L. Van Der Plas, T. P. Vogels, and S. G. Manohar, “Predictive learning enables neural networks to learn complex working memory tasks,” in Proceedings of Machine Learning Research, 2022, vol. 199, pp. 518–531.

M. Lechner, A. Amini, D. Rus, and T. A. Henzinger, “Revisiting the adversarial robustness-accuracy tradeoff in robot learning,” arXiv. .

C. Schreck and C. Wojtan, “Coupling 3D liquid simulation with 2D wave propagation for large scale water surface animation using the equivalent sources method,” Computer Graphics Forum, vol. 41, no. 2. Wiley, pp. 343–353, 2022.

R. Takhanov and V. Kolmogorov, “Combining pattern-based CRFs and weighted context-free grammars,” Intelligent Data Analysis, vol. 26, no. 1. IOS Press, pp. 257–272, 2022.

G. Valperga and M. de Bono, “Impairing one sensory modality enhances another by reconfiguring peptidergic signalling in Caenorhabditis elegans,” eLife, vol. 11. eLife Sciences Publications, 2022.

G. Ivanov and M. Naszódi, “Functional John ellipsoids,” Journal of Functional Analysis, vol. 282, no. 11. Elsevier, 2022.

M. Obr, W. J. H. Hagen, R. A. Dick, L. Yu, A. Kotecha, and F. K. Schur, “Exploring high-resolution cryo-ET and subtomogram averaging capabilities of contemporary DEDs,” Journal of Structural Biology, vol. 214, no. 2. Elsevier, 2022.

S. J. Henheik and R. Tumulka, “Interior-boundary conditions for the Dirac equation at point sources in three dimensions,” Journal of Mathematical Physics, vol. 63, no. 12. AIP Publishing, 2022.

W. F. Mlynarski and G. Tkadik, “Efficient coding theory of dynamic attentional modulation,” PLoS Biology, vol. 20, no. 12. Public Library of Science, p. e3001889, 2022.

S. E. Ojavee, Z. Kutalik, and M. R. Robinson, “Liability-scale heritability estimation for biobank studies of low-prevalence disease,” The American Journal of Human Genetics, vol. 109, no. 11. Elsevier, pp. 2009–2017, 2022.

R. Hasani et al., “Closed-form continuous-time neural networks,” Nature Machine Intelligence, vol. 4, no. 11. Springer Nature, pp. 992–1003, 2022.

R. Guerrini et al., “Phenotypic and genetic spectrum of ATA encephalopathy: A disorder of lysosomal homeostasis,” Brain, vol. 145, no. 8. Oxford University Press, pp. 2687–2703, 2022.

S. Kovadid et al., “Carbon foams via ring-opening metathesis polymerization of emulsion templates: A facile method to make carbon current collectors for battery applications,” ACS Applied Energy Materials, vol. 5, no. 11. American Chemical Society, pp. 14381–14390, 2022.

N. Doan, S. A. Hashemi, M. Mondelli, and W. J. Gross, “Decoding Reed-Muller codes with successive codeword permutations,” IEEE Transactions on Communications, vol. 70, no. 11. Institute of Electrical and Electronics Engineers, pp. 7134–7145, 2022.

A. J. Johnson et al., “Three-dimensional visualization of planta clathrin-coated vesicles at ultrastructural resolution,” Molecular Plant, vol. 15, no. 10. Elsevier, pp. 1533–1542, 2022.

D. Brückner et al., “Geometry adaptation of protrusion and polarity dynamics in confined cell migration,” Physical Review X, vol. 12, no. 3. American Physical Society, 2022.

E. B. Iofinova, E.-A. Peste, M. Kurtz, and D.-A. Alistarh, “How well do sparse ImageNet models transfer?,” in 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition, New Orleans, LA, United States, 2022, pp. 12256–12266.

G. Cipolloni, L. Erdös, and D. J. Schröder, “Optimal multi-resolvent local laws for Wigner matrices,” Electronic Journal of Probability, vol. 27. Institute of Mathematical Statistics, pp. 1–38, 2022.

N. Rahaman et al., “Neural attentive circuits,” in 36th Conference on Neural Information Processing Systems, New Orleans, United States, 2022, vol. 35.

P. Rao et al., “VoRF: Volumetric Relightable Faces,” in 33rd British Machine Vision Conference, London, United Kingdom, 2022.

K. Bartalska et al., “A systematic characterization of microglia-like cell occurrence during retinal organoid differentiation,” iScience, vol. 25, no. 7. Elsevier, 2022.

S. Tasciyan, “Role of microenvironment heterogeneity in cancer cell invasion,” Institute of Science and Technology Austria, 2022.

P. Velicky et al., “Saturated reconstruction of living brain tissue,” bioRxiv. Cold Spring Harbor Laboratory.

J. M. Michalska et al., “Uncovering brain tissue architecture across scales with super-resolution light microscopy,” bioRxiv. Cold Spring Harbor Laboratory.

T. Hoefler, D.-A. Alistarh, T. Ben-Nun, N. Dryden, and E.-A. Peste, “Sparsity in deep learning: Pruning and growth for efficient inference and training in neural networks,” Journal of Machine Learning Research, vol. 22, no. 241. Journal of Machine Learning Research, pp. 1–124, 2021.

Z. Babaiee, R. Hasani, M. Lechner, D. Rus, and R. Grosu, “On-off center-surround receptive fields for accurate and robust image classification,” in Proceedings of the 38th International Conference on Machine Learning, Virtual, 2021, vol. 139, pp. 478–489.

F. Lombardi, S. Pepic, O. Shriki, G. Tkadik, and D. De Martino, “Quantifying the coexistence of neuronal oscillations and avalanches.” arXiv.

R. Bacon et al., “The MUSE Extremely Deep Field: The cosmic web in emission at high redshift,” Astronomy &; Astrophysics, vol. 647. EDP Sciences, 2021.

J. J. Matthee et al., “The X-SHOOTER Lyman ;1 survey at z = 2 (XLS-z2) I: What makes a galaxy a Lyman ;1 emitter?,” Monthly Notices of the Royal Astronomical Society, vol. 505, no. 1. Oxford University Press, pp. 1382–1412, 2021.

S. G. Gallego et al., “Constraining the cosmic UV background at z &; 3 with MUSE Lyman-;1 emission observations,” Monthly Notices of the Royal Astronomical Society, vol. 504, no. 1. Oxford University Press, pp. 16–32, 2021.

L. comi, R. Zrour, G. Largeteau-Skapin, R. Biswas, and E. Andres, “Body centered cubic grid - coordinate system and discrete analytical plane definition,” in Discrete Geometry and Mathematical Morphology, Uppsala, Sweden, 2021, vol. 12708, pp. 152–163.

H. Li et al., “Cellular requirements for PIN polar cargo clustering in Arabidopsis thaliana,” New Phytologist, vol. 229, no. 1. Wiley, pp. 351–369, 2021.

S. E. Ojavee et al., “Genomic architecture and prediction of censored time-to-event phenotypes with a Bayesian genome-wide analysis,” Nature Communications, vol. 12, no. 1. Nature Research, 2021.

S. Arnoux, C. Fraisse, and C. Sauvage, “Genomic inference of complex domestication histories in three Solanaceae species,” Journal of Evolutionary Biology, vol. 34, no. 2. Wiley, pp. 270–283, 2021.

S. Hankeova et al., “DUCT reveals architectural mechanisms contributing to bile duct recovery in a mouse model for alagille syndrome,” eLife, vol. 10. eLife Sciences Publications, 2021.

O. Elek et al., “Robust and practical measurement of volume transport parameters in solid photo-polymer materials for 3D printing,” Optics Express, vol. 29, no. 5. The Optical Society, pp. 7568–7588, 2021.

A. M. Arroyo Guevara, D. Mcquillan, R. B. Richter, G. Salazar, and M. Sullivan, “Drawings of complete graphs in the projective plane,” Journal of Graph Theory, vol. 97, no. 3. Wiley, pp. 426–440, 2021.

F. R. Gärtner and M. K. Sixt, “Engaging the front wheels to drive through fibrous terrain,” Developmental Cell, vol. 56, no. 6. Elsevier, pp. 723–725, 2021.

R. Zhang, T. Auzinger, and B. Bickel, “Computational design of planar multistable compliant structures,” ACM Transactions on Graphics, vol. 40, no. 5. Association for Computing Machinery, 2021.

G. Cipolloni, L. Erdös, and D. J. Schröder, “Fluctuation around the circular law for random matrices with real entries,” Electronic Journal of Probability, vol. 26. Institute of Mathematical Statistics, 2021.

Q. Yang et al., “Cell fate coordinates mechano-osmotic forces in intestinal crypt formation,” Nature Cell Biology, vol. 23. Springer Nature, pp. 733–744, 2021.

A. Serrano et al., “The effect of shape and illumination on material perception: Model and applications,” ACM Transactions on Graphics, vol. 40, no. 4. Association for Computing Machinery, 2021.

A. Chaigne, M. B. Smith, R. L. Cavestany, E. B. Hannezo, K. J. Chalut, and E. K. Paluch, “Three-dimensional geometry controls division symmetry in stem cell colonies,” Journal of Cell Science, vol. 134, no. 14. The Company of Biologists, 2021.

T. Rittig et al., “Neural acceleration of scattering-aware color 3D printing,” Computer Graphics Forum, vol. 40, no. 2. Wiley, pp. 205–219, 2021.

P. Sahu, J. M. Schwarz, and M. L. Manning, “Geometric signatures of tissue surface tension in a three-dimensional model of confluent tissue,” New Journal of Physics, vol. 23, no. 9. IOP Publishing, 2021.

I. Sudec, B. Bersch, and P. Schanda, “How do chaperones bind (partly) unfolded client proteins?,” Frontiers in Molecular Biosciences, vol. 8. Frontiers, 2021.

S. Sietzen, M. Lechner, J. Borowski, R. Hasani, and M. Waldner, “Interactive analysis of CNN robustness,” Computer Graphics Forum, vol. 40, no. 7. Wiley, pp. 253–264, 2021.

A. Ghazaryan, E. M. Nica, O. Erten, and P. Ghaemi, “Shadow surface states in topological Kondo insulators,” New Journal of Physics, vol. 23, no. 12. IOP Publishing, 2021.

G. Dresdner, S. Shekhar, F. Pedregosa, F. Locatello, and G. Rätsch, “Boosting variational inference with locally adaptive step-sizes,” in Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, Montreal, Canada, 2021, pp. 2337–2343.

N. Rahaman et al., “Dynamic inference with neural interpreters,” in Advances in Neural Information Processing Systems, Virtual, 2021, vol. 34, pp. 10985–10998.

B. Scholkopf et al., “Toward causal representation learning,” Proceedings of the IEEE, vol. 109, no. 5. Institute of Electrical and Electronics Engineers, pp. 612–634, 2021.

M. Patxot et al., “Probabilistic inference of the genetic architecture underlying functional enrichment of complex traits,” Nature Communications, vol. 12, no. 1. Springer Nature, 2021.

M. R. Robinson, “Probabilistic inference of the genetic architecture of functional enrichment of complex traits.” Dryad, 2021.

W. F. Mlynarski, M. Hledik, T. R. Sokolowski, and G. Tkadik, “Statistical analysis and optimality of neural systems,” Neuron, vol. 109, no. 7. Cell Press, p. 1227–1241.e5, 2021.

M. F. Nabais et al., “Significant out-of-sample classification from methylation profile scoring for amyotrophic lateral sclerosis,” npj Genomic Medicine, vol. 5. Springer Nature, 2020.

R. J. Beattie, S. Hippenmeyer, and F. Pauler, “SCOPES: Sparking curiosity through Open-Source platforms in education and science,” Frontiers in Education, vol. 5. Frontiers Media, 2020.

R. Biswas, G. Largeteau-Skapin, R. Zrour, and E. Andres, “Digital objects in rhombic dodecahedron grid,” Mathematical Morphology - Theory and Applications, vol. 4, no. 1. De Gruyter, pp. 143–158, 2020.

V. Aksenov, D.-A. Alistarh, and J. Korhonen, “Scalable belief propagation via relaxed scheduling,” in Advances in Neural Information Processing Systems, Vancouver, Canada, 2020, vol. 33, pp. 22361–22372.

F. Laccone et al., “A bending-active twisted-arch plywood structure: Computational design and fabrication of the FlexMaps Pavilion,” SN Applied Sciences, vol. 2, no. 9. Springer Nature, 2020.

M. Kurtz et al., “Inducing and exploiting activation sparsity for fast neural network inference,” in 37th International Conference on Machine Learning, ICML 2020, Online, 2020, vol. 119, pp. 5533–5543.

P. M. Henderson and C. Lampert, “Unsupervised object-centric video generation and decomposition in 3D,” in 34th Conference on Neural Information Processing Systems, Vancouver, Canada, 2020, vol. 33, pp. 3106–3117.

S. Arnoux, C. Fraisse, and C. Sauvage, “VCF files of synonymous SNPs related to: Genomic inference of complex domestication histories in three Solanaceae species.” Dryad, 2020.

P. M. Henderson and V. Ferrari, “Learning single-image 3D reconstruction by generative modelling of shape, pose and shading,” International Journal of Computer Vision, vol. 128. Springer Nature, pp. 835–854, 2020.

P. Dodier et al., “Single-stage bone resection and cranioplastic reconstruction: Comparison of a novel software-derived PEEK workflow with the standard reconstructive method,” International Journal of Oral and Maxillofacial Surgery, vol. 49, no. 8. Elsevier, pp. 07-1015, 2020.

P. J. Gonçalves et al., “Training deep neural density estimators to identify mechanistic models of neural dynamics,” eLife, vol. 9. eLife Sciences Publications, 2020.

C. Prehal et al., “Persistent and reversible solid iodine electrodeposition in nanoporous carbons,” Nature Communications, vol. 11. Springer Nature, 2020.

C. Henneberger et al., “LTP induction boosts glutamate spillover by driving withdrawal of perisynaptic astroglia,” Neuron, vol. 108, no. 5. Elsevier, p. 9–936., 2020.

S.  Galan, N. N. Machnik, K. Kruse, N. Díaz, M. A. Marti-Renom, and J. M. Vaquerizas, “CHESS enables quantitative comparison of chromatin contact data and automatic feature extraction,” Nature Genetics, vol. 52. Springer Nature, pp. 1247–1255, 2020.

J. A. P. L.-S. Jamie A. P. Law-Smith et al., “Successful common envelope ejection and binary neutron star formation in 3D hydrodynamics,” arXiv. .

L. Bossmann, “Derivation of the 2d Gross–Pitaevskii equation for strongly confined 3d Bosons,” Archive for Rational Mechanics and Analysis, vol. 238, no. 11. Springer Nature, pp. 541–606, 2020.

R. Grah, B. Zoller, and G. Tkadik, “Normative models of enhancer function,” bioRxiv. Cold Spring Harbor Laboratory, 2020.

R. Zhang, “Structure-aware computational design and its application to 3D printable volume scattering, mechanism, and multistability,” Institute of Science and Technology Austria, 2020.

P. M. Henderson, V. Tsiminaki, and C. Lampert, “Leveraging 2D data to learn textured 3D mesh generation,” in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, Virtual, 2020, pp. 7498–7507.

F. K. Schur, “STL-files for 3D-printed grid holders described in  Fäßler F, Zens B, et al.; 3D printed cell culture grid holders for improved cellular specimen preparation in cryo-electron microscopy.” Institute of Science and Technology Austria, 2020.

J. E. Salazar et al., “Anatomical specializations related to foraging in the visual system of a nocturnal insectivorous bird, the band-winged nightjar (Aves: Caprimulgiformes),” Brain, Behavior and Evolution, vol. 94, no. 1–4. Karger Publishers, pp. 27–36, 2020.

U. Bauer, H. Edelsbrunner, G. Jablonski, and M. Mrozek, “cech-Delaunay gradient flow and homology inference for self-maps,” Journal of Applied and Computational Topology, vol. 4, no. 4. Springer Nature, pp. 455–480, 2020.

F. Fäßler, B. Zens, R. Hauschild, and F. K. Schur, “D printed cell culture grid holders for improved cellular specimen preparation in cryo-electron microscopy,” Journal of Structural Biology, vol. 212, no. 3. Elsevier, 2020.

L. Harker-Kirschneck, B. Baum, and A. Sari, “Changes in ESCRT-III filament geometry drive membrane remodelling and fission in silico,” BMC Biology, vol. 17, no. 1. Springer Nature, 2019.

A. Buchwalter, J. M. Kaneshiro, and M. Hetzer, “Coaching from the sidelines: The nuclear periphery in genome regulation,” Nature Reviews Genetics, vol. 20, no. 1. Springer Nature, pp. 39–50, 2019.

Y. Asaoka, H. Morita, H. Furumoto, C.-P. J. Heisenberg, and M. Furutani-Seiki, “Studying YAP-mediated 3D morphogenesis using fish embryos and human spheroids,” in The hippo pathway, vol. 1893, A. Hergovich, Ed. Springer, 2019, pp. 167–181.

R. Biswas, G. Largeteau-Skapin, R. Zrour, and E. Andres, “Rhombic dodecahedron grid—coordinate system and 3D digital object definitions,” in 21st IAPR International Conference on Discrete Geometry for Computer Imagery, Marne-la-Vallée, France, 2019, vol. 11414, pp. 27–37.

M. Renzo et al., “Massive runaway and walkaway stars,” Astronomy &; Astrophysics, vol. 624. EDP Sciences, 2019.

A. Traxl et al., “Inhibition of ABC and ABC at the mouse blood-brain barrier with marketed drugs to improve brain delivery of the model ABC/ABC substrate [11C]erlotinib,” Molecular Pharmaceutics, vol. 16, no. 3. American Chemical Society, pp. 1282–1293, 2019.

F. K. Schur, “Toward high-resolution in situ structural biology with cryo-electron tomography and subtomogram averaging,” Current Opinion in Structural Biology, vol. 58, no. 10. Elsevier, pp. 1–9, 2019.

T. Éltes, M. Szoboszlay, M. K. Szigeti, and Z. Nusser, “Improved spike inference accuracy by estimating the peak amplitude of unitary [C+] transients in weakly GCaMf-expressing hippocampal pyramidal cells,” Journal of Physiology, vol. 597, no. 11. Wiley, pp. 2925–2947, 2019.

J. Guiu et al., “Tracing the origin of adult intestinal stem cells,” Nature, vol. 570. Springer Nature, pp. 107–111, 2019.

D. Sumin et al., “Geometry-aware scattering compensation for 3D printing,” ACM Transactions on Graphics, vol. 38, no. 4. ACM, 2019.

B. Oliveira, A. Ç. Yahya, and G. Novarino, “Modeling cell-cell interactions in the brain using cerebral organoids,” Brain Research, vol. 1724. Elsevier, 2019.

O. Ovaskainen, J. Rybicki, and N. Abrego, “What can observational data reveal about metacommunity processes?,” Ecography, vol. 42, no. 11. Wiley, pp. 1877–1886, 2019.

K. Yamada and M. K. Sixt, “Mechanisms of 3D cell migration,” Nature Reviews Molecular Cell Biology, vol. 20, no. 12. Springer Nature, pp. 738–752, 2019.

A. R. Rueda Sanchez, W. J. Hease, S. Barzanjeh, and J. M. Fink, “Electro-optic entanglement source for microwave to telecom quantum state transfer,” npj Quantum Information, vol. 5. Springer Nature, 2019.

T. R. Sokolowski et al., GFRD in all dimensions,” The Journal of Chemical Physics, vol. 150, no. 5. AIP Publishing, 2019.

P. Swoboda and V. Kolmogorov, “Map inference via block-coordinate Frank-Wolfe algorithm,” in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Long Beach, CA, United States, 2019, vol. 2019–June.

F. Laccone et al., “FlexMaps Pavilion: A twisted arc made of mesostructured flat flexible panels,” in IASS Symposium 2019 - 60th Anniversary Symposium of the International Association for Shell and Spatial Structures; Structural Membranes 2019 - 9th International Conference on Textile Composites and Inflatable Structures, FORM and FORCE, Barcelona, Spain, 2019, pp. 509–515.

N. H. Barton and A. Etheridge, “Mathematical models in population genetics,” in Handbook of statistical genomics, 4th ed., D. Balding, I. Moltke, and J. Marioni, Eds. Wiley, 2019, pp. 115–144.

M. W. Gondal et al., “On the transfer of inductive bias from simulation to the real world: a new disentanglement dataset,” in Advances in Neural Information Processing Systems, Vancouver, Canada, 2019, vol. 32.

E. FAS et al., “Custom-size, functional, and durable DNA origami with design-specific scaffolds,” ACS Nano, vol. 13, no. 5. ACS Publications, pp. 5015–5027, 2019.

F. P. Assen, “Lymph node mechanics: Deciphering the interplay between stroma contractility, morphology and lymphocyte trafficking,” Institute of Science and Technology Austria, 2019.

J. Kühnen, D. Scarselli, and B. Hof, “Relaminarization of pipe flow by means of 3D-printed shaped honeycombs,” Journal of Fluids Engineering, vol. 141, no. 11. ASME, 2019.

C. Hafner, C. Schumacher, E. Knoop, T. Auzinger, B. Bickel, and M. Bächer, “X-CAD: Optimizing CAD Models with Extended Finite Elements,” ACM Transactions on Graphics, vol. 38, no. 6. ACM, 2019.

F. Mohammadi, C. Uhler, C. Wang, and J. Yu, “Generalized permutohedra from probabilistic graphical models,” SIAM Journal on Discrete Mathematics, vol. 32, no. 1. SIAM, pp. 64–93, 2018.

J. J. Matthee, D. Sobral, M. Gronke, A. Paulino-Afonso, M. Stefanon, and H. Röttgering, “Confirmation of double peaked Ly;1 emission at z = 6.593: Witnessing a galaxy directly contributing to the reionisation of the universe,” Astronomy &; Astrophysics, vol. 619. EDP Sciences, 2018.

J. J. Matthee and J. Schaye, “Star-forming galaxies are predicted to lie on a fundamental plane of mass, star formation rate, and ;1-enhancement,” Monthly Notices of the Royal Astronomical Society: Letters, vol. 479, no. 1. Oxford University Press, pp. L34–L39, 2018.

G. Raskutti and C. Uhler, “Learning directed acyclic graphs based on sparsest permutations,” STAT, vol. 7, no. 1. Wiley, 2018.

A. De Martino and D. De Martino, “An introduction to the maximum entropy approach and its application to inference problems in biology,” Heliyon, vol. 4, no. 4. Elsevier, 2018.

G. Koshti, R. Biswas, G. Largeteau-Skapin, R. Zrour, E. Andres, and P. Bhowmick, “Sphere construction on the FCC grid interpreted as layered hexagonal grids in 3D,” in 19th International Workshop, Porto, Portugal, 2018, vol. 11255, pp. 82–96.

A. Shekhovtsov, P. Swoboda, and B. Savchynskyy, “Maximum persistency via iterative relaxed inference with graphical models,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 40, no. 7. IEEE, pp. 1668–1682, 2018.

J. Zeng et al., “Signatures of negative selection in the genetic architecture of human complex traits,” Nature Genetics, vol. 50, no. 5. Springer Nature, pp. 746–753, 2018.

A. Polino, R. Pascanu, and D.-A. Alistarh, “Model compression via distillation and quantization,” in 6th International Conference on Learning Representations, Vancouver, Canada, 2018.

P. Buri and F. Pellicciotti, “Aspect controls the survival of ice cliffs on debris-covered glaciers,” PNAS, vol. 115, no. 17. Proceedings of the National Academy of Sciences, pp. 4369–4374, 2018.

M. Iglesias Ham, “Multiple covers with balls,” Institute of Science and Technology Austria, 2018.

J. Masís, D. Mankus, S. Wolff, G. Guitchounts, M. A. Jösch, and D. Cox, “A micro-CT-based method for quantitative brain lesion characterization and electrode localization,” Scientific Reports, vol. 8, no. 1. Nature Publishing Group, 2018.

M. M. Napiórkowski, R. Reuvers, and J. Solovej, “Calculation of the critical temperature of a dilute Bose gas in the Bogoliubov approximation,” EPL, vol. 121, no. 1. IOP Publishing Ltd., 2018.

P. Mohapatra, M. Rolinek, C. V. Jawahar, V. Kolmogorov, and M. P. Kumar, “Efficient optimization for rank-based loss functions,” in 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, Salt Lake City, UT, USA, 2018, pp. 3693–3701.

H. Ringbauer, A. Kolesnikov, D. Field, and N. H. Barton, “Estimating barriers to gene flow from distorted isolation-by-distance patterns,” Genetics, vol. 208, no. 3. Genetics Society of America, pp. 1231–1245, 2018.

F. Locatello, G. Dresdner, R. Khanna, I. Valera, and G. Rätsch, “Boosting black box variational inference,” in Advances in Neural Information Processing Systems, Montreal, Canada, 2018, vol. 31.

F. Locatello, R. Khanna, J. Ghosh, and G. Rätsch, “Boosting variational inference: An optimization perspective,” in Proceedings of the 21st International Conference on Artificial Intelligence and Statistics, Playa Blanca, Lanzarote, 2018, vol. 84, pp. 464–472.

T. Alderighi, L. Malomo, D. Giorgi, N. Pietroni, B. Bickel, and P. Cignoni, “Metamolds: Computational design of silicone molds,” ACM Trans. Graph., vol. 37, no. 4. ACM, 2018.

J. Renkawitz, A. Reversat, A. F. Leithner, J. Merrin, and M. K. Sixt, “Micro-engineered ‘pillar forests’ to study cell migration in complex but controlled 3D environments,” in Methods in Cell Biology, vol. 147, Academic Press, 2018, pp. 79–91.

C. Frick et al., “Nano-scale microfluidics to study 3D chemotaxis at the single cell level,” PLoS One, vol. 13, no. 6. Public Library of Science, 2018.

J. Higareda Almaraz et al., “Norepinephrine triggers an immediate-early regulatory network response in primary human white adipocytes,” BMC Genomics, vol. 19, no. 1. BioMed Central, 2018.

K. Bod’Ová, G. Mitchell, R. Harpaz, E. Schneidman, and G. Tkadik, “Probabilistic models of individual and collective animal behavior,” PLoS One, vol. 13, no. 3. Public Library of Science, 2018.

K. Bod’Ová, G. Mitchell, R. Harpaz, E. Schneidman, and G. Tkadik, “Implementation of the inference method in Matlab.” Public Library of Science, 2018.

S. Hille, M. Akhmanova, M. Glanc, A. J. Johnson, and J. Friml, “Relative contribution of PIN-containing secretory vesicles and plasma membrane PINs to the directed auxin transport: Theoretical estimation,” International Journal of Molecular Sciences, vol. 19, no. 11. MDPI, 2018.

K. Sawada, R. Kawakami, R. Shigemoto, and T. Nemoto, “Super resolution structural analysis of dendritic spines using three-dimensional structured illumination microscopy in cleared mouse brain slices,” European Journal of Neuroscience, vol. 47, no. 9. Wiley, pp. 1033–1042, 2018.

L. Malomo et al., “FlexMaps: Computational design of flat flexible shells for shaping 3D objects,” ACM Transactions on Graphics, vol. 37, no. 6. Association for Computing Machinery (ACM), 2018.

S. Haller, P. Swoboda, and B. Savchynskyy, “Exact MAP-inference by confining combinatorial search with LP relaxation,” in Proceedings of the 32st AAAI Conference on Artificial Intelligence, New Orleans, LU, United States, 2018, pp. 6581–6588.

B. Bickel, P. Cignoni, L. Malomo, and N. Pietroni, “State of the art on stylized fabrication,” Computer Graphics Forum, vol. 37, no. 6. Wiley, pp. 325–342, 2018.

H. Ringbauer, “Inferring recent demography from spatial genetic structure,” Institute of Science and Technology Austria, 2018.

S. Reipert et al., “Agitation modules: Flexible means to accelerate automated freeze substitution,” Journal of Histochemistry and Cytochemistry, vol. 66, no. 12. SAGE Publications, pp. 903–921, 2018.

J. Masís, D. Mankus, S. Wolff, G. Guitchounts, M. A. Jösch, and D. Cox, “A micro-CT-based method for characterising lesions and locating electrodes in small animal brains,” Journal of visualized experiments, vol. 141. MyJove Corporation, 2018.

C. Fraisse et al., “The divergence history of European blue mussel species reconstructed from Approximate Bayesian Computation: The effects of sequencing techniques and sampling strategies,” PeerJ, vol. 2018, no. 7. PeerJ, 2018.

T. Ellis, D. Field, and N. H. Barton, “Efficient inference of paternity and sibship inference given known maternity via hierarchical clustering,” Molecular Ecology Resources, vol. 18, no. 5. Wiley, pp. 988–999, 2018.

T. Ellis, “Data and Python scripts supporting Python package FAPS.” Institute of Science and Technology Austria, 2018.

R. K. Kelemen and B. Vicoso, “Complex history and differentiation patterns of the t-haplotype, a mouse meiotic driver,” Genetics, vol. 208, no. 1. Genetics Society of America, pp. 365–375, 2018.

A. Stroe, D. Sobral, J. J. Matthee, J. Calhau, and I. Oteo, “A 1.4 de blind survey for C II], C III] and C IV at z c 0.7–1.5 – II. Luminosity functions and cosmic average line ratios,” Monthly Notices of the Royal Astronomical Society, vol. 471, no. 3. Oxford University Press, pp. 2575–2586, 2017.

M. Bächer, B. Bickel, E. Whiting, and O. Sorkine Hornung, “Spin it: Optimizing moment of inertia for spinnable objects,” Communications of the ACM, vol. 60, no. 8. ACM, pp. 92–99, 2017.

P. Nam and M. M. Napiórkowski, “Bogoliubov correction to the mean-field dynamics of interacting bosons,” Advances in Theoretical and Mathematical Physics, vol. 21, no. 3. International Press, pp. 683–738, 2017.

R. Biswas and P. Bhowmick, “On the functionality and usefulness of Quadraginta octants of naive sphere,” Journal of Mathematical Imaging and Vision, vol. 59, no. 1. Springer Nature, pp. 69–83, 2017.

R. Biswas, P. Bhowmick, and V. E. Brimkov, “On the polyhedra of graceful spheres and circular geodesics,” Discrete Applied Mathematics, vol. 216. Elsevier, pp. 362–375, 2017.

S. Dwivedi, A. Gupta, S. Roy, R. Biswas, and P. Bhowmick, “Fast and Efficient Incremental Algorithms for Circular and Spherical Propagation in Integer Space,” in 20th IAPR International Conference, Vienna, Austria, 2017, vol. 10502, pp. 347–359.

R. Biswas and P. Bhowmick, “Construction of persistent Voronoi diagram on 3D digital plane,” in Combinatorial image analysis, vol. 10256, Cham: Springer Nature, 2017, pp. 93–104.

J. Kuske, P. Swoboda, and S. Petra, “A novel convex relaxation for non binary discrete tomography,” presented at the SSVM: Scale Space and Variational Methods in Computer Vision, Kolding, Denmark, 2017, vol. 10302, pp. 235–246.

Y. Wang, M. Nagarajan, C. Uhler, and G. Shivashankar, “Orientation and repositioning of chromosomes correlate with cell geometry dependent gene expression,” Molecular Biology of the Cell, vol. 28, no. 14. American Society for Cell Biology, pp. 1997–2009, 2017.

E. Morris et al., “Shaping 3D root system architecture,” Current Biology, vol. 27, no. 17. Cell Press, pp. 9–0, 2017.

L. Yengo et al., “Detection and quantification of inbreeding depression for complex traits from SNP data,” Proceedings of the National Academy of Sciences, vol. 114, no. 32. Proceedings of the National Academy of Sciences, pp. 8602–8607, 2017.

L. R. Lloyd-Jones et al., “Inference on the genetic basis of eye and skin color in an admixed population via Bayesian linear mixed models,” Genetics, vol. 206, no. 2. Genetics Society of America, pp. 1113–1126, 2017.

J. W. Rocks, N. Pashine, I. Bischofberger, C. P. Goodrich, A. J. Liu, and S. R. Nagel, “Designing allostery-inspired response in mechanical networks,” Proceedings of the National Academy of Sciences, vol. 114, no. 10. Proceedings of the National Academy of Sciences, pp. 2520–2525, 2017.

B. Turoová, F. K. Schur, W. Wan, and J. Briggs, “Efficient 3D-CTF correction for cryo-electron tomography using NovaCTF improves subtomogram averaging resolution to 3.4Å,” Journal of Structural Biology, vol. 199, no. 3. Academic Press, pp. 187–195, 2017.

J. Singer, T. W. Grunt, E. Jensen-Jarolim, and J. Singer, “Long term storage in liquid nitrogen leads to only minor phenotypic and gene expression changes in the mammary carcinoma model cell line ,” Oncotarget, vol. 8. Impact Journals, pp. 35076–35087, 2017.

H. Fraga et al., “Solidstate NMR H–N–(C)–H and H–N–C–C 3D/4D correlation experiments for resonance assignment of large proteins,” ChemPhysChem, vol. 18, no. 19. Wiley, pp. 2697–2703, 2017.

M. J. Chalk, P. Masset, B. Gutkin, and S. Denève, “Sensory noise predicts divisive reshaping of receptive fields,” PLoS Computational Biology, vol. 13, no. 6. Public Library of Science, 2017.

O. Elek et al., “Scattering-aware texture reproduction for 3D printing,” ACM Transactions on Graphics, vol. 36, no. 6. ACM, 2017.

H. Ringbauer, G. Coop, and N. H. Barton, “Inferring recent demography from isolation by distance of long shared sequence blocks,” Genetics, vol. 205, no. 3. Genetics Society of America, pp. 1335–1351, 2017.

R. Zhang, T. Auzinger, D. Ceylan, W. Li, and B. Bickel, “Functionality-aware retargeting of mechanisms to 3D shapes,” presented at the SIGGRAPH: Computer Graphics and Interactive Techniques, Los Angeles, CA, United States , 2017, vol. 36, no. 4.

R. Guseinov, E. Miguel, and B. Bickel, “CurveUps: Shaping objects from flat plates with tension-actuated curvature,” presented at the SIGGRAPH: Special Interest Group on Computer Graphics and Interactive Techniques, Los Angeles, CA, United States, 2017, vol. 36, no. 4.

I. Cherepanov and M. Lemeshko, “Fingerprints of angulon instabilities in the spectra of matrix-isolated molecules,” Physical Review Materials, vol. 1, no. 3. American Physical Society, 2017.

D. Kainmueller, F. Jug, C. Rother, and G. Meyers, “Graph matching problems for annotating C. Elegans.” Institute of Science and Technology Austria, 2017.

C. Uhler and G. V. Shivashankar, “Geometric control and modeling of genome reprogramming,” BioArchitecture, vol. 6, no. 4. Taylor &; Francis, pp. 76–84, 2016.

L. Malomo, N. Pietroni, B. Bickel, and P. Cignoni, “FlexMolds: Automatic design of flexible shells for molding,” presented at the SIGGRAPH Asia: Conference and Exhibition on Computer Graphics and Interactive Techniques in Asia, Macao, China, 2016, vol. 35, no. 6.

C. Savin and G. Tkadik, “Estimating nonlinear neural response functions using GP priors and Kronecker methods,” presented at the NIPS: Neural Information Processing Systems, Barcelona; Spain, 2016, vol. 29, pp. 3610–3618.

A. Rueda et al., “Efficient single sideband microwave to optical conversion using a LiNbO WGM-resonator,” presented at the CLEO: Conference on Lasers and Electro Optics, San Jose, CA, USA, 2016.

M. Bächer et al., “DefSense: computational design of customized deformable input devices,” presented at the CHI: Conference on Human Factors in Computing Systems, San Jose, California, USA, 2016, pp. 3806–3816.

K. Lohse, M. Chmelik, S. Martin, and N. H. Barton, “Efficient strategies for calculating blockwise likelihoods under the coalescent,” Genetics, vol. 202, no. 2. Genetics Society of America, pp. 775–786, 2016.

C. Schilling, S. Bogomolov, T. A. Henzinger, A. Podelski, and J. Ruess, “Adaptive moment closure for parameter inference of biochemical reaction networks,” Biosystems, vol. 149. Elsevier, pp. 15–25, 2016.

R. Biswas and P. Bhowmick, “On functionality of quadraginta octants of naive sphere with application to circle drawing,” in Discrete Geometry for Computer Imagery, Nantes, France, 2016, vol. 9647, pp. 256–267.

R. Biswas, P. Bhowmick, and V. E. Brimkov, “On the connectivity and smoothness of discrete spherical circles,” in Combinatorial image analysis, vol. 9448, Cham: Springer Nature, 2016, pp. 86–100.

A. Potter, M. Serbyn, and A. Vishwanath, “Thermoelectric transport signatures of Dirac composite fermions in the half-filled Landau level,” Physical Review X, vol. 6, no. 3. American Physical Society, 2016.

T. Monk, C. Savin, and J. Lücke, “Neurons equipped with intrinsic plasticity learn stimulus intensity statistics,” presented at the NIPS: Neural Information Processing Systems, Barcelona, Spaine, 2016, vol. 29, pp. 4285–4293.

V. Kolmogorov and R. Takhanov, “Inference algorithms for pattern-based CRFs on sequence data,” Algorithmica, vol. 76, no. 1. Springer, pp. 17–46, 2016.

A. Rueda et al., “Efficient microwave to optical photon conversion: An electro-optical realization,” Optica, vol. 3, no. 6. Optica Publishing Group, pp. 597–604, 2016.

E. Stahl, F. M. Praetorius, C. C. de Oliveira Mann, K.-P. Hopfner, and H. Dietz, “Impact of heterogeneity and lattice bond strength on DNA triangle crystal growth,” ACS Nano, vol. 10, no. 10. American Chemical Society, pp. 9156–9164, 2016.

T. G. Martin et al., “Design of a molecular support for cryo-EM structure determination,” PNAS, vol. 113, no. 47. Proceedings of the National Academy of Sciences, pp. 56–63, 2016.

D. Field and T. Ellis, “Inference of mating patterns among wild snapdragons in a natural hybrid zone in 2012.” Institute of Science and Technology Austria, 2016.

F. Parise, J. Lygeros, and J. Ruess, “Bayesian inference for stochastic individual-based models of ecological systems: a pest control simulation study,” Frontiers in Environmental Science, vol. 3. Frontiers, 2015.

R. Colini-Baldeschi, S. Leonardi, M. H. Henzinger, and M. Starnberger, “On multiple keyword sponsored search auctions with budgets,” ACM Transactions on Economics and Computation, vol. 4, no. 1. Association for Computing Machinery, 2015.

J. Reininghaus, S. Huber, U. Bauer, and R. Kwitt, “A stable multi-scale kernel for topological machine learning,” presented at the CVPR: Computer Vision and Pattern Recognition, Boston, MA, USA, 2015, pp. 4741–4748.

J. Ruess, F. Parise, A. Milias Argeitis, M. Khammash, and J. Lygeros, “Iterative experiment design guides the characterization of a light-inducible gene expression circuit,” PNAS, vol. 112, no. 26. National Academy of Sciences, pp. 8148–8153, 2015.

R. Fulek and R. Radoidi, “Vertical visibility among parallel polygons in three dimensions,” in Graph Drawing and Network Visualization, vol. 9411, Springer Nature, 2015, pp. 373–379.

A. Bermano, T. Beeler, Y. Kozlov, D. Bradley, B. Bickel, and M. Gross, “Detailed spatio-temporal reconstruction of eyelids,” presented at the SIGGRAPH: Special Interest Group on Computer Graphics and Interactive Techniques, Los Angeles, CA, United States, 2015, vol. 34, no. 4.

C. Schumacher, B. Bickel, J. Rys, S. Marschner, C. Daraio, and M. Gross, “Microstructures to control elasticity in 3D printing,” presented at the SIGGRAPH: Special Interest Group on Computer Graphics and Interactive Techniques, Los Angeles, CA, USA, 2015, vol. 34, no. 4.

P. Guerrero, S. Jeschke, M. Wimmer, and P. Wonka, “Learning shape placements by example,” presented at the SIGGRAPH: Special Interest Group on Computer Graphics and Interactive Techniques, Los Angeles, CA, United States, 2015, vol. 34, no. 4.

S. Bogomolov, T. A. Henzinger, A. Podelski, J. Ruess, and C. Schilling, “Adaptive moment closure for parameter inference of biochemical reaction networks,” vol. 9308. Springer, pp. 77–89, 2015.

B. Vicoso and D. Bachtrog, “Numerous transitions of sex chromosomes in Diptera,” PLoS Biology, vol. 13, no. 4. Public Library of Science, 2015.

S. Porazinski et al., “YAP is essential for tissue tension to ensure vertebrate 3D body shape,” Nature, vol. 521, no. 7551. Nature Publishing Group, pp. 217–221, 2015.

J. Ruess and J. Lygeros, “Moment-based methods for parameter inference and experiment design for stochastic biochemical reaction networks,” ACM Transactions on Modeling and Computer Simulation, vol. 25, no. 2. ACM, 2015.

C. N. Boccara, L. Kjønigsen, I. Hammer, J. Bjaalie, T. Leergaard, and M. Witter, “A three-plane architectonic atlas of the rat hippocampal region,” Hippocampus, vol. 25, no. 7. Wiley, pp. 838–857, 2015.

A. Kremer et al., “Developing 3D SEM in a broad biological context,” Journal of Microscopy, vol. 259, no. 2. Wiley-Blackwell, pp. 80–96, 2015.

A. Gupta, T. A. Henzinger, A. Radhakrishna, R. Samanta, and T. Tarrach, “Succinct representation of concurrent trace sets,” presented at the POPL: Principles of Programming Languages, Mumbai, India, 2015, pp. 433–444.

J. Reiter et al., Reconstructing robust phylogenies of metastatic cancers. IST Austria, 2015.

D. Caruntu, T. Rostamzadeh, T. Costanzo, S. Salemizadeh Parizi, and G. Caruntu, “Solvothermal synthesis and controlled self-assembly of monodisperse titanium-based perovskite colloidal nanocrystals,” Nanoscale, vol. 7, no. 30. RSC, pp. 12955–12969, 2015.

O. Symonova, C. Topp, and H. Edelsbrunner, “DynamicRoots: A software platform for the reconstruction and analysis of growing plant roots,” PLoS One, vol. 10, no. 6. Public Library of Science, 2015.

B. Trubenova, S. Novak, and R. Hager, “Mathematical inference of the results.” Public Library of Science, 2015.

V. Ruprecht et al., “Cortical contractility triggers a stochastic switch to fast amoeboid cell motility,” Cell, vol. 160, no. 4. Cell Press, pp. 673–685, 2015.

J. Kasten, J. Reininghaus, W. Reich, and G. Scheuermann, “Toward the extraction of saddle periodic orbits,” in Topological Methods in Data Analysis and Visualization III , vol. 1, P.-T. Bremer, I. Hotz, V. Pascucci, and R. Peikert, Eds. Cham: Springer, 2014, pp. 55–69.

A. Gordon, T. A. Henzinger, A. Nori, and S. Rajamani, “Probabilistic programming,” in Proceedings of the on Future of Software Engineering, Hyderabad, India, 2014, pp. 167–181.

A. Gupta, L. Kovács, B. Kragl, and A. Voronkov, “Extensional crisis and proving identity,” in ATVA 2014, Sydney, Australia, 2014, vol. 8837, pp. 185–200.

D. Günther, A. Jacobson, J. Reininghaus, H. Seidel, O. Sorkine Hornung, and T. Weinkauf, “Fast and memory-efficient topological denoising of 2D and 3D scalar fields,” IEEE Transactions on Visualization and Computer Graphics, vol. 20, no. 12. IEEE, pp. 2585–2594, 2014.

S. Lin, C. Uhler, B. Sturmfels, and P. Bühlmann, “Hypersurfaces and their singularities in partial correlation testing,” Foundations of Computational Mathematics, vol. 14, no. 5. Springer, pp. 1079–1116, 2014.

M. Marchand, S. Hongyu, E. Morvant, J. Rousu, and J. Shawe Taylor, “Multilabel structured output learning with random spanning trees of max-margin Markov networks,” presented at the NIPS: Neural Information Processing Systems, 2014.

K. Raveendran, C. Wojtan, N. Thuerey, and G. Türk, “Blending liquids,” in ACM Transactions on Graphics, Vancouver, Canada, 2014, vol. 33, no. 4.

M. Skouras et al., “Designing inflatable structures,” presented at the SIGGRAPH: Special Interest Group on Computer Graphics and Interactive Techniques, 2014, vol. 33, no. 4.

M. BacHer, E. Whiting, B. Bickel, and O. Sorkine Hornung, “Spin-It: Optimizing moment of inertia for spinnable objects,” presented at the SIGGRAPH: 41st International Conference and Exhibition on Computer Graphics and Interactive Techniques, 2014, vol. 33, no. 4.

A. Kolesnikov, M. Guillaumin, V. Ferrari, and C. Lampert, “Closed-form approximate CRF training for scalable image segmentation,” in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Zurich, Switzerland, 2014, vol. 8691, no. PART 3, pp. 550–565.

E. Cires Rodriguez, M. Baltisberger, C. Cuesta, P. Vargas, and J. Prieto, “Allopolyploid origin of the Balkan endemic Ranunculus wettsteinii (Ranunculaceae) inferred from nuclear and plastid DNA sequences,” Organisms Diversity and Evolution, vol. 14, no. 1. Springer, pp. 1–10, 2014.

F. Zhu et al., “DICE, an efficient system for iterative genomic editing in human pluripotent stem cells,” Nucleic Acids Research, vol. 42, no. 5. Oxford University Press, 2014.

R. Biswas and P. Bhowmick, “On Finding Spherical Geodesic Paths and Circles in 3,” vol. 8668. Springer, Berlin, Heidelberg, pp. 396–409, 2014.

E. B. Hannezo, J. Prost, and J. Joanny, “Theory of epithelial sheet morphology in three dimensions,” PNAS, vol. 111, no. 1. National Academy of Sciences, pp. 27–32, 2014.

J. Hearn, G. Stone, L. Bunnefeld, J. Nicholls, N. H. Barton, and K. Lohse, “Likelihood-based inference of population history from low-coverage de novo genome assemblies,” Molecular Ecology, vol. 23, no. 1. Wiley-Blackwell, pp. 198–211, 2014.

D. Sobral et al., “The dynamics of z=0.8 H-alpha-selected star-forming galaxies from KMOS/CF-HiZELS,” The Astrophysical Journal, vol. 779, no. 2. IOP Publishing, 2013.

C. Uhler, G. Raskutti, P. Bühlmann, and B. Yu, “Geometry of the faithfulness assumption in causal inference,” The Annals of Statistics, vol. 41, no. 2. Institute of Mathematical Statistics, pp. 436–463, 2013.

S. Coros et al., “Computational design of mechanical characters,” ACM Transactions on Graphics, vol. 32, no. 4. ACM, 2013.

O. Rouiller, B. Bickel, J. Kautz, W. Matusik, and M. Alexa, “D printing spatially varying BRDFs,” IEEE Computer Graphics and Applications, vol. 33, no. 6. IEEE, pp. 48–57, 2013.

B. Bickel and M. Alexa, “Computational aspects of fabrication: Modeling, design and 3d printing,” IEEE Computer Graphics and Applications, vol. 33, no. 6. IEEE, pp. 24–25, 2013.

T. Auzinger, M. Wimmer, and S. Jeschke, “Analytic Visibility on the GPU,” Computer Graphics Forum, vol. 32, no. 124. Wiley-Blackwell, pp. 409–418, 2013.

M. Valderrama, V. Botella Soler, and M. Le Van Quyen, “Neuronal oscillations scale up and scale down the brain dynamics ,” in Multiscale Analysis and Nonlinear Dynamics: From Genes to the Brain, M. Meyer and Z. Pesenson, Eds. Wiley-VCH, 2013.

R. Piskac, T. Wies, and D. Zufferey, “Automating separation logic using SMT,” vol. 8044. Springer, pp. 773–789, 2013.

I. Sanchez-Romero et al., “Mechanism of protein kinetic stabilization by engineered disulfide crosslinks,” PLoS One, vol. 8, no. 7. Public Library of Science, 2013.

N. Quadrianto, V. Sharmanska, D. Knowles, and Z. Ghahramani, “The supervised IBP: Neighbourhood preserving infinite latent feature models,” in Proceedings of the 29th conference uncertainty in Artificial Intelligence, Bellevue, WA, United States, 2013, pp. 527–536.

K. Landberg et al., “The moss physcomitrella patens reproductive organ development is highly organized, affected by the two SHI/STY genes and by the level of active auxin in the SHI/STY expression domain,” Plant Physiology, vol. 162, no. 3. American Society of Plant Biologists, pp. 1406–1419, 2013.

K. Rajan, O. Marre, and G. Tkadik, “Learning quadratic receptive fields from neural responses to natural stimuli,” Neural Computation, vol. 25, no. 7. MIT Press , pp. 1661–1692, 2013.

C. Topp et al., “D phenotyping and quantitative trait locus mapping identify core regions of the rice genome controlling root architecture,” PNAS, vol. 110, no. 18. National Academy of Sciences, pp. 95–04, 2013.

N. H. Barton, A. Etheridge, J. Kelleher, and A. Véber, “Inference in two dimensions: Allele frequencies versus lengths of shared sequence blocks,” Theoretical Population Biology, vol. 87, no. 1. Elsevier, pp. 105–119, 2013.

M. Kerber and H. Edelsbrunner, “D kinetic alpha complexes and their implementation,” in 2013 Proceedings of the 15th Workshop on Algorithm Engineering and Experiments, New Orleans, LA, United States, 2013, pp. 70–77.

E. Kodama-Namba, L. A. Fenk, A. J. Bretscher, E. Gross, K. E. Busch, and M. de Bono, “Cross-modulation of homeostatic responses to temperature, oxygen and carbon dioxide in C. elegans,” PLoS Genetics, vol. 9, no. 12. Public Library of Science (PLoS), 2013.

S. Aeschbacher, A. Futschik, and M. Beaumont, “Approximate Bayesian computation for modular inference problems with many parameters: the example of migration rates. ,” Molecular Ecology, vol. 22, no. 4. Wiley-Blackwell, pp. 987–1002, 2013.

J. Hearn, G. Stone, N. H. Barton, K. Lohse, and L. Bunnefeld, “Data from: Likelihood-based inference of population history from low coverage de novo genome assemblies.” Dryad, 2013.

M. Weber and M. K. Sixt, “Live Cell Imaging of Chemotactic Dendritic Cell Migration in Explanted Mouse Ear Preparations,” in Chemokines, vol. 1013, A. Cardona and E. Ubogu, Eds. Totowa, NJ: Humana Press, 2013, pp. 215–226.

R. Takhanov and V. Kolmogorov, “Inference algorithms for pattern-based CRFs on sequence data,” in ICML’13 Proceedings of the 30th International Conference on International, Atlanta, GA, USA, 2013, vol. 28, no. 3, pp. 145–153.

R. Colini-Baldeschi, M. H. Henzinger, S. Leonardi, and M. Starnberger, “On multiple keyword sponsored search auctions with budgets,” in 39th International Colloquium on Automata, Languages, and Programming, Warwick, United Kingdom, 2012, vol. 7392, pp. 1–12.

K. Hildebrand, B. Bickel, and M. Alexa, “crdbrd: Shape fabrication by sliding planar slices,” Computer Graphics Forum, vol. 31, no. 2pt3. Wiley-Blackwell, pp. 583–592, 2012.

T. Beeler et al., “Coupled 3D reconstruction of sparse facial hair and skin,” ACM Transactions on Graphics, vol. 31, no. 4. ACM, 2012.

M. BacHer, B. Bickel, D. James, and H. Pfister, “Fabricating articulated characters from skinned meshes,” ACM Transactions on Graphics, vol. 31, no. 4. ACM, 2012.

B. Bickel et al., “Physical face cloning,” ACM Transactions on Graphics, vol. 31, no. 4. ACM, 2012.

E. Miguel et al., “Data-driven estimation of cloth simulation models,” presented at the Computer Graphics Forum, 2012, vol. 31, no. 2, pp. 519–528.

T. Auzinger, M. Guthe, and S. Jeschke, “Analytic anti-aliasing of linear functions on polytopes,” presented at the EUROGRAPHICS: European Association for Computer Graphics, 2012, vol. 31, no. 121, pp. 335–344.

T. Budisantoso, K. Matsui, N. Kamasawa, Y. Fukazawa, and R. Shigemoto, “Mechanisms underlying signal filtering at a multisynapse contact,” Journal of Neuroscience, vol. 32, no. 7. Society for Neuroscience, pp. 2357–2376, 2012.

C. Lampert, “Dynamic pruning of factor graphs for maximum marginal prediction,” presented at the NIPS: Neural Information Processing Systems, Lake Tahoe, NV, United States, 2012, vol. 1, pp. 82–90.

V. Kolmogorov and T. Schoenemann, “Generalized sequential tree-reweighted message passing,” arXiv. ArXiv, 2012.

M. Blaschko and C. Lampert, “Guest editorial: Special issue on structured prediction and inference,” International Journal of Computer Vision, vol. 99, no. 3. Springer, pp. 257–258, 2012.

A. Ion, J. Carreira, and C. Sminchisescu, “Image segmentation by figure-ground composition into maximal cliques,” presented at the ICCV: International Conference on Computer Vision, Barcelona, Spain, 2012.

C. Lampert and J. Peters, “Real-time detection of colored objects in multiple camera streams with off-the-shelf hardware components,” Journal of Real-Time Image Processing, vol. 7, no. 1. Springer, pp. 31–41, 2012.

G. Rieckh, W. Kreuzer, H. Waubke, and P. Balazs, “A 2.5D-Fourier-BEM model for vibrations in a tunnel running through layered anisotropic soil,”  Engineering Analysis with Boundary Elements, vol. 36, no. 6. Elsevier, pp. 960–967, 2012.

F. Korc, V. Kolmogorov, and C. Lampert, “Approximating marginals using discrete energy minimization,” presented at the ICML: International Conference on Machine Learning, Edinburgh, Scotland, 2012.

F. Korc, V. Kolmogorov, and C. Lampert, Approximating marginals using discrete energy minimization. IST Austria, 2012.

E. Rennella, T. Cutuil, P. Schanda, I. Ayala, V. Forge, and B. Brutscher, “Real-time NMR characterization of structure and dynamics in a transiently populated protein folding intermediate,” Journal of the American Chemical Society, vol. 134, no. 19. American Chemical Society, pp. 8066–8069, 2012.

S. Aeschbacher, A. Futschik, and M. Beaumont, “Data from: Approximate Bayesian computation for modular inference problems with many parameters: the example of migration rates.” Dryad, 2012.

A. Osokin, D. Vetrov, and V. Kolmogorov, “Submodular decomposition framework for inference in associative Markov networks with global constraints,” presented at the CVPR: Computer Vision and Pattern Recognition, 2011, pp. 1889–1896.

D. Tarlow, D. Batra, P. Kohli, and V. Kolmogorov, “Dynamic tree block coordinate ascent,” presented at the ICML: International Conference on Machine Learning, 2011, pp. 113–120.

M. K. Sixt and T. Lämmermann, “In vitro analysis of chemotactic leukocyte migration in 3D environments,” Cell Migration, vol. 769. Springer, pp. 149–165, 2011.

H. Wagner, C. Chen, and E. Vuçini, “Efficient computation of persistent homology for cubical data,” in Topological Methods in Data Analysis and Visualization II, R. Peikert, H. Hauser, H. Carr, and R. Fuchs, Eds. Springer, 2011, pp. 91–106.

Y. Zheng, S. Gu, H. Edelsbrunner, C. Tomasi, and P. Benfey, Detailed reconstruction of 3D plant root shape. IEEE, 2011.

M. Huber et al., “A proton-detected 4D solid-state NMR experiment for protein structure determination,” ChemPhysChem, vol. 12, no. 5. Wiley, pp. 915–918, 2011.

S. Nowozin and C. Lampert, “Structured learning and prediction in computer vision,” Foundations and Trends in Computer Graphics and Vision, vol. 6, no. 3–4. Now Publishers, pp. 185–365, 2011.

B. Bickel, “Measurement-based modeling and fabrication of deformable materials for human faces,” Unknown, 2010.

T. Beeler, B. Bickel, P. Beardsley, B. Sumner, and M. Groß, “High-quality single-shot capture of facial geometry,” ACM Transactions on Graphics, vol. 29, no. 4. ACM, 2010.

B. Bickel et al., “Design and fabrication of materials with desired deformation behavior,” ACM Transactions on Graphics, vol. 29, no. 4. ACM, 2010.

S. Nowozin and C. Lampert, “Global interactions in random field models: A potential function ensuring connectedness,” SIAM Journal on Imaging Sciences, vol. 3, no. 4 (Special Section on Optimization in Imaging Sciences). Society for Industrial and Applied Mathematics , pp. 1048–1074, 2010.

M. Weber and M. K. Sixt, “MEK signalling tunes actin treadmilling for interstitial lymphocyte migration,” EMBO Journal, vol. 29, no. 17. Wiley-Blackwell, pp. 2861–2863, 2010.

T. A. Henzinger, T. Hottelier, L. Kovács, and A. Voronkov, “Invariant and type inference for matrices,” presented at the VMCAI: Verification, Model Checking and Abstract Interpretation, Madrid, Spain, 2010, vol. 5944, pp. 163–179.

K. P. Weber, S. De, I. Kozarewa, D. J. Turner, M. M. Babu, and M. de Bono, “Whole genome sequencing highlights genetic changes associated with laboratory domestication of C. elegans,” PLoS ONE, vol. 5, no. 11. Public Library of Science, 2010.

A. Giuliani and R. Seiringer, “The ground state energy of the weakly interacting Bose gas at high density,” Journal of Statistical Physics, vol. 135, no. 5–6. Springer, pp. 915–934, 2009.

O. Woodford, C. Rother, and V. Kolmogorov, “A global perspective on MAP inference for low level vision,” presented at the ICCV: International Conference on Computer Vision, 2009, pp. 2319–2326.

M. Blaschko and C. Lampert, “Object localization with global and local context kernels,” presented at the BMVC: British Machine Vision Conference, 2009, pp. 1–11.

C. Lampert and J. Peters, A high-speed object tracker from off-the-shelf components. IEEE, 2009.

S. Kryazhimskiy, G. Tkadik, and J. Plotkin, “The dynamics of adaptation on correlated fitness landscapes,” PNAS, vol. 106, no. 44. National Academy of Sciences, pp. 18638–18643, 2009.

T. Quast et al., “Cytohesin-1 controls the activation of RhoA and modulates integrin-dependent adhesion and migration of dendritic cells,” Blood, vol. 113, no. 23. American Society of Hematology, pp. 5801–5810, 2009.

G. Soete and C.-P. J. Heisenberg, “The role of the extracellular matrix in Kupffer’s vesicle formation in zebrafish,” Mechanisms of Development, vol. 126. Elsevier, pp. 8–8, 2009.

C. Lampert and M. Blaschko, “Structured prediction by joint kernel support estimation,” Machine Learning, vol. 77, no. 2–3. Springer, pp. 249–269, 2009.

S. Nowozin and C. Lampert, “Global connectivity potentials for random field models,” presented at the CVPR: Computer Vision and Pattern Recognition, 2009, pp. 818–825.

S. Lahiri, S. Qadeer, J. Galeotti, J. Voung, and T. Wies, “Intra-module Inference,” presented at the CAV: Computer Aided Verification, 2009, pp. 493–508.

A. Rastelli et al., “Three-dimensional composition profiles of single quantum dots determined by scanning-probe-microscopy-based nanotomography,” Nano Letters, vol. 8, no. 5. American Chemical Society, pp. 1404–1409, 2008.

A. Podelski, A. Rybalchenko, and T. Wies, “Heap Assumptions on Demand,” presented at the CAV: Computer Aided Verification, 2008, vol. 5123, pp. 314–327.

L. V. Ugelvig, F. Drijfhout, D. Kronauer, J. Boomsma, J. Pedersen, and S. Cremer, “The introduction history of invasive garden ants in Europe: integrating genetic, chemical and behavioural approaches,” BMC Biology, vol. 6, no. 11. BioMed Central, 2008.

N. Pietroni, M. Otaduy, B. Bickel, F. Ganovelli, and M. Groß, “Texturing internal surfaces from a few cross-sections,” Computer Graphics Forum, vol. 26, no. 3. Wiley-Blackwell, pp. 637–644, 2007.

V. Kolmogorov, Y. Boykov, and C. Rother, “Applications of parametric maxflow in computer vision,” presented at the ICCV: International Conference on Computer Vision, 2007.

E. Lescop, P. Schanda, and B. Brutscher, “A set of BEST triple-resonance experiments for time-optimized protein resonance assignment,” Journal of Magnetic Resonance, vol. 187, no. 1. Elsevier, pp. 163–169, 2007.

B. Bickel, M. Wicke, and M. Gross, “Adaptive simulation of electrical discharges,” presented at the VMV: Vision, Modeling, and Visualization, 2006.

T. Weyrich et al., “Analysis of human faces using a measurement-based skin reflectance model,” ACM Transactions on Graphics, vol. 25, no. 3. ACM, pp. 1013–1024, 2006.

T. Weyrich et al., “Analysis of human faces using a measurement-based skin reflectance model,” presented at the ACM SIGGRAPH, 2006, pp. 1013–1024.

C. Rother, V. Kolmogorov, T. Minka, and A. Blake, “Cosegmentation of image pairs by histogram matching - Incorporating a global constraint into MRFs,” presented at the CVPR: Computer Vision and Pattern Recognition, 2006, pp. 993–1000.

C. Lampert and T. Breuel, “Objective quality measurement for geometric document image restoration,” presented at the DAS: Document Analysis Systems, 2006.

Y. Boykov, V. Kolmogorov, D. Cremers, and A. Delong, “An integral solution to surface evolution PDEs via geo cuts,” presented at the ECCV: European Conference on Computer Vision, 2006, vol. 3953, pp. 409–422.

Y. Fletcher, T. Gloth, H. Edelsbrunner, and P. Fu, “Method, apparatus and computer products that reconstruct surfaces from data points.” 2006.

M. Drumea Mirancea et al., “Characterization of a conduit system containing laminin-5 in the human thymus: a potential transport system for small molecules,” Journal of Cell Science, vol. 119, no. Pt 7. Company of Biologists, pp. 1396–1405, 2006.

O. Hosten, M. Rakher, J. Barreiro, N. Peters, and P. Kwiat, “Counterfactual quantum computation through quantum interrogation,” Nature, vol. 439, no. 7079. Nature Publishing Group, pp. 949–952, 2006.

B. Nürnberger, N. H. Barton, L. Kruuk, and T. Vines, “Mating patterns in a Bombina hybrid zone: Inferences from adult and full sib genotypes,” Heredity, vol. 94, no. 2. Nature Publishing Group, pp. 247–257, 2005.

M. K. Sixt et al., “The conduit system transports soluble antigens from the afferent lymph to resident dendritic cells in the T cell area of the lymph node,” Immunity, vol. 22, no. 1. Cell Press, pp. 19–29, 2005.

A. Ulges, C. Lampert, and T. Breuel, “Document capture using stereo vision,” presented at the DocEng: ACM Symposium on Document Engineering, 2004, pp. 198–200.

T. A. Henzinger, R. Jhala, and R. Majumdar, “Race checking by context inference,” presented at the PLDI: Programming Languages Design and Implementation, 2004, pp. 1–13.

A. Panchenko, F. Kondrashov, and S. Bryant, “Prediction of functional sites by analysis of sequence and structure conservation,” Protein Science, vol. 13, no. 4. Wiley-Blackwell, pp. 884–892, 2004.

É. Lieb, R. Seiringer, and J. Yngvason, “One-dimensional Bosons in three-dimensional traps,” Physical Review Letters, vol. 91, no. 15. American Physical Society, pp. 1504011–1504014, 2003.

M. T. Bollenbach, T. Strother, and W. Bauer, “D supernova collapse calculations,” presented at the NATO ASI on Structure and Dynamics of Elementary Matter, 2003, vol. 166, pp. 277–288.

Y. Boykov and V. Kolmogorov, “Computing geodesics and minimal surfaces via graph cuts,” presented at the ICCV: International Conference on Computer Vision, 2003, vol. 1, pp. 26–33.

O. Hosten, P. Vignolo, A. Minguzzi, B. Tanatar, and M. Tosi, “Free expansion of two-dimensional condensates with a vortex,” Journal of Physics B: Atomic, Molecular and Optical Physics, vol. 36, no. 12. IOP Publishing Ltd., pp. 2455–2463, 2003.

J. Harshman, C. Huddleston, J. P. Bollback, T. Parsons, and M. Braun, “True and false gharials: A nuclear gene phylogeny of crocodylia,” Systematic Biology, vol. 52, no. 3. Oxford University Press, pp. 386–402, 2003.

J. P. Bollback, “Bayesian model adequacy and choice in phylogenetics,” Molecular Biology and Evolution, vol. 19, no. 7. Oxford University Press, pp. 1171–80, 2002.

J. Bischofberger, J. Geiger, and P. M. Jonas, “Timing and efficacy of Ca(2+) channel activation in hippocampal mossy fiber boutons,” Journal of Neuroscience, vol. 22, no. 24. Society for Neuroscience, pp. 10593–10602, 2002.

M. T. Bollenbach and W. Bauer, “d supernovae collapse calculations,” presented at the CRIS: Catania Relativistic Ion Studies , Catania, Italy, 2002, vol. 644, pp. 219–232.

J. Kitano et al., “Tamalin, a PDZ domain-containing protein, links a protein complex formation of group 1 metabotropic glutamate receptors and the guanine nucleotide exchange factor cytohesins,” Journal of Neuroscience, vol. 22, no. 4. Society for Neuroscience, pp. 1280–1289, 2002.

J. Huelsenbeck, F. Ronquist, R. Nielsen, and J. P. Bollback, “Bayesian inference of phylogeny and its impact on evolutionary biology,” Science, vol. 294, no. 5550. American Association for the Advancement of Science, pp. 2310–2314, 2001.

J. Huelsenbeck and J. P. Bollback, “Application of the likelihood function in phylogenetic analysis,” in Handbook of Statistical Genetics, D. Balding, M. Bishop, and C. Cannings, Eds. Wiley-Blackwell, 2001, pp. 415–439.

G. Sansig et al., “Increased seizure susceptibility in mice lacking metabotropic glutamate receptor 7,” Journal of Neuroscience, vol. 21, no. 22. Society for Neuroscience, pp. 8734–8745, 2001.

É. Lieb, R. Seiringer, and J. Yngvason, “A rigorous derivation of the Gross-Pitaevskii energy functional for a two-dimensional Bose gas,” Communications in Mathematical Physics, vol. 224, no. 1. Springer, pp. 17–31, 2001.

N. H. Barton and L. Partridge, “Limits to natural selection,” BioEssays, vol. 22, no. 12. Wiley-Blackwell, pp. 1075–1084, 2000.

N. H. Barton, “Estimating multilocus linkage disequilibria,” Heredity, vol. 84, no. 3. Nature Publishing Group, pp. 373–389, 2000.

C. Normann, D. Peckys, C. Schulze, J. Walden, P. M. Jonas, and J. Bischofberger, “Associative long-term depression in the hippocampus is dependent on postsynaptic N-type Ca(2+) channels,” Journal of Neuroscience, vol. 20, no. 22. Society for Neuroscience, pp. 8290–8297, 2000.

L. A. Sazanov and J. Walker, “Cryo-electron crystallography of two sub-complexes of bovine complex I reveals the relationship between the membrane and peripheral arms,” Journal of Molecular Biology, vol. 302, no. 2. Elsevier, pp. 455–464, 2000.

H. Edelsbrunner, M. Facello, P. Fu, J. Qian, and D. Nekhayev, “Wrapping 3D scanning data,” presented at the Three-Dimensional Image Capture and Applications, 1998, vol. 3313, pp. 148–158.

T. Götz, U. Kraushaar, J. Geiger, J. Lubke, T. Berger, and P. M. Jonas, “Functional properties of AMPA and NMDA receptors expressed in identified types of basal ganglia neurons,” Journal of Neuroscience, vol. 17, no. 1. Society for Neuroscience, pp. 204–215, 1997.

N. Akkiraju, H. Edelsbrunner, P. Fu, and J. Qian, “Viewing geometric protein structures from inside a CAVE,” IEEE Computer Graphics and Applications, vol. 16, no. 4. IEEE, pp. 58–61, 1996.

N. Spruston, P. M. Jonas, and B. Sakmann, “Dendritic glutamate receptor channels in rat hippocampal C and C pyramidal neurons,” Journal of Physiology, vol. 482, no. Pt 2. Wiley-Blackwell, pp. 325–352, 1995.

J. Sites, N. H. Barton, and K. Reed, “The genetic structure of a mosaic hybrid zone between two chromosome races of the Sceloporus grammicus complex (Sauria, Phrynosomatidae) in central Mexico,” Evolution, vol. 49, no. 1. Wiley-Blackwell, pp. 9–36, 1995.

P. M. Jonas, G. Major, and B. Sakmann, “Quantal components of unitary EPSCs at the mossy fibre synapse on C pyramidal cells of rat hippocampus,” Journal of Physiology, vol. 472. Wiley-Blackwell, pp. 615–663, 1993.

J. Szymura and N. H. Barton, “The genetic structure of the hybrid zone between the fire-bellied toads Bombina bombina and B. variegata: comparisons between transects and between loci,” Evolution, vol. 45, no. 2. Wiley-Blackwell, pp. 237–261, 1991.

M. Bräu, F. Dreyer, P. M. Jonas, H. Repp, and W. Vogel, “A K+ channel in Xenopus nerve fibres selectively blocked by bee and snake toxins: binding and voltage-clamp experiments,” Journal of Physiology, vol. 420. Wiley-Blackwell, pp. 365–385, 1990.

J. Mallet and N. H. Barton, “Inference from clines stabilized by frequency-dependent selection,” Genetics, vol. 122, no. 4. Genetics Society of America, pp. 967–976, 1989.

P. M. Jonas, “Temperature dependence of gating current in myelinated nerve fibers,” Journal of Membrane Biology, vol. 112, no. 3. Springer, pp. 277–289, 1989.