@inproceedings{22894,
  abstract     = {Large-scale deep learning models are known to memorize parts of the training
set. In machine learning theory, memorization is often framed as interpolation or
label fitting, and classical results show that this can be achieved when the number
of parameters p in the model is larger than the number of training samples n. In
this work, we consider memorization from the perspective of data reconstruction,
demonstrating that this can be achieved when p is larger than dn, where d is
the dimensionality of the data. More specifically, we show that, in the random
features model, when p ≫ dn, the subspace spanned by the training samples in
feature space gives sufficient information to identify the individual samples in input
space. Our analysis suggests an optimization method to reconstruct the dataset
from the model parameters, and we demonstrate that this method performs well on
various architectures (random features, two-layer fully-connected and deep residual
networks). Our results reveal a law of data reconstruction, according to which the
entire training dataset can be recovered as p exceeds the threshold dn.
},
  author       = {Iurada, Leonardo and Bombari, Simone and Tommasi, Tatiana and Mondelli, Marco},
  booktitle    = {14th International Conference on Learning Representations},
  isbn         = {9798331339678},
  location     = {Rio de Janeiro, Brazil},
  pages        = {145275--145314},
  publisher    = {OpenReview},
  title        = {{A law of data reconstruction for random features (and beyond)}},
  volume       = {2026},
  year         = {2026},
}

@inproceedings{22921,
  abstract     = {Runtime monitoring of quantitative signals faces a fundamental trade-off between volatility and over-aggregation: instantaneous observations are noisy, while long-run averages obscure local structure. Localisation measures such as discounted averages offer a principled middle ground, yet remain poorly understood in runtime verification. This paper studies discounted sums from a monitoring perspective, in both deterministic and stochastic settings. We formalize the discounted monitoring problem and show that exact, sound monitoring of discounted sums cannot be achieved with finite memory. To overcome this impossibility, we introduce ε-approximately sound monitoring, deriving explicit bounds on memory and observation requirements. We then extend the framework to stochastic processes via expected discounted sums, defining pointwise and uniform (ε,δ)-soundness notions, establishing statistical optimality, and proving impossibility beyond a precision threshold. We also formalize the resource complexity of deterministic discounted monitoring via affine register machines and prove a tight worst-case lower bound. Finally, we present a specification language for arithmetic expressions over multiple discounted sums with synchronous and asynchronous semantics, and evaluate our approach on practical scenarios including algorithmic fairness.},
  author       = {Cano Cordoba, Filip and Henzinger, Thomas A and Kueffner, Konstantin and Sarac, Naci E},
  booktitle    = {37th International Conference on Concurrency Theory},
  isbn         = {9783959774475},
  issn         = {1868-8969},
  keywords     = {Runtime Verification, Probabilistic Systems, Quantitative Verification, Approximate Monitoring},
  location     = {Liverpool, United Kingdom},
  publisher    = {Schloss Dagstuhl - Leibniz-Zentrum für Informatik},
  title        = {{Monitoring discounted sum properties}},
  doi          = {10.4230/LIPIcs.CONCUR.2026.22},
  volume       = {391},
  year         = {2026},
}

@article{22957,
  abstract     = {Linguistic inequality remains a silent barrier in contemporary science, particularly in rapidly evolving and interdisciplinary fields such as bioinformatics. This article examines how the Spanish-speaking community has responded to this gap through the creation of the Simposio de Estudiantes Hispanohablantes de Bioinformática y Biología Computacional (SEH2Bioinfo), a collective initiative that transforms language into a tool for inclusion and collaboration. Drawing on a historical review of the use of Spanish in scientific communication and an analysis of the two editions of SEH2Bioinfo (2022 and 2025), complemented by surveys of more than 1500 participants, we explore the effects of language on confidence, participation, and academic visibility. The findings show that Spanish can serve as a space for training and mentorship without compromising rigor, while simultaneously strengthening international networks and promoting open science. The growth of SEH2Bioinfo, its collaborative approach, and its intercontinental reach establish the symposium as a model for linguistic equity in scientific practice. Its experience demonstrates that expanding linguistic diversity in bioinformatics is not only possible but essential to building a global scientific community that is fairer, more connected, and representative.},
  author       = {Padilla Franzotti, Carla L and Olguín-Orellana, Gabriel J and Palopoli, Nicolas and Urquiza-Zurich, Sebastián and Garcia-Moreno, Adrian and Monzón, Sara and Cabrera-Pasadas, Mónica and Soler Sáez, Irene and Perpiñá-Clérigues, Carla and Puche Quiñonez, Rafael J and Vélez Segura, Jennifer and Lovaco-Flores, Jose Abel and Osorio Mogollón, Cleidy M and Esquinas-Román, Eva M and Miserendino, Maria C and Eranti, Pradeep and Castillo-Orozco, Ana and Cuesta-Astroz, Yesid and Parra, R Gonzalo},
  issn         = {2635-0041},
  journal      = {Bioinformatics Advances},
  number       = {1},
  publisher    = {Oxford University Press},
  title        = {{Bioinformatics in Español: Expanding open, diverse, and collaborative science through SEH2Bioinfo}},
  doi          = {10.1093/bioadv/vbag182},
  volume       = {6},
  year         = {2026},
}

@phdthesis{21198,
  abstract     = {In recent years there has been a massive increase in the amount of data generated in a
decentralized manner. Ever more powerful edge devices, such as smartphones, have become
ubiquitous in most societies on earth. Through text typed, photos taken and apps used,
these devices, which we refer to as clients, generate enormous amounts of high quality and
complex data. Moreover, the nature of these devices means the data they generate is often
sensitive and privacy concerns prevent it being gathered and stored in a central location. This
presents a challenge to the modern machine learning paradigm that requires central access
to large amounts of data. Federated learning (FL) has emerged as one of the answers to
this problem. Rather than bringing the data to the model, FL sends the model to the data.
Model training takes place on device, with periodically synchronized updates, allowing data to
remain locally stored. While this approach offers significant privacy advantages it comes with
its own set of unique challenges. These include: data heterogeneity, the notion that different
devices generate data in distinct ways which can negatively impact training dynamics; systems
heterogeneity, meaning that different devices may have differing hardware specifications; high
communication costs, which are induced by the repeated transferring of models over the
network and low device computational power, which limits the use of larger models on device.
In this thesis we present a range of methods for federated learning. We focus primarily on
the challenge of data heterogeneity, though the methods presented are designed to be well
adapted to the other challenges of a federated setting, such as the constraints of limited
compute and communication overhead. We first present a method for explicitly modeling client
data heterogeneity. The approach formulates clients as samples from a certain probability
distribution and infers the parameters of this distribution from the available training clients.
This learned distribution then represents the heterogeneity present among the clients and can
be sampled from in order to create new simulated clients that are similar to the real clients we
have observed so far. Following this we present two methods for directly dealing with data
heterogeneity through personalization. Highly heterogeneous client data distributions can mean
that learning a single global model becomes suboptimal, and some form of personalization of
models to each individual client is required. Our approaches are based around hypernetworks,
which we use to generate personalized model parameters without the need for additional
training or finetuning. In the first approach we focus on generating full parameterizations of
client models using learned embeddings of client data and labels, with a hypernetwork located
on the central server. In the second approach we address the more challenging scenario where
we want to generate a personalized model for a client without any label information. The
hypernetwork is trained to generate a low dimensional representation of a client’s personalized
model parameters, allowing it to be transferred to and run on the client devices. In our final
presented method, we change our focus and rather than aim to directly address the challenge
of data heterogeneity, we instead ensure we are unaffected by it. This is done in the context
of k-means clustering and we present a method for federated clustering with a focus on added
privacy guarantees.},
  author       = {Scott, Jonathan A},
  issn         = {2663-337X},
  pages        = {158},
  publisher    = {Institute of Science and Technology Austria},
  title        = {{Data heterogeneity and personalization in federated learning}},
  doi          = {10.15479/AT-ISTA-21198},
  year         = {2026},
}

@phdthesis{21854,
  abstract     = {As neural-network-based models grow both in size and popularity, interest has grown in making the models smaller and more efficient to train. To that end, many methods have been proposed to prune models by reducing their number of nonzero parameters. Additionally, parameter-efficient fine-tuning, in which a much smaller number of parameters than the total contained in the model is updated during training, has become very popular, especially in the space of Large Language Models. At the same time, the increasingly routine deployment of machine learning in real-world applications has spurred a drive to make them more trustworthy - in the sense of, among other things, being unbiased, interpretable, and editable. In this thesis, we examine the interplay between efficiency and trustworthiness.

First, we analyze the effects of model pruning on bias in computer vision models, demonstrating that increased sparsity leads to greater bias, largely as a function of increased model uncertainty in marginal cases. Based on this observation, we propose several bias mitigation techniques. Then, we demonstrate that example-specific model pruning can improve model interpretation methods while improving pruning efficiency to make example-specific model pruning feasible in real time. Then, we investigate the effectiveness of parameter-efficient and data-efficient model personalization via fine-tuning, demonstrating that it is highly feasible with very small computational and data resources. Finally, we consider efficiency in editing model knowledge using a custom synthetic data framework, demonstrating that parameter-efficient, low-rank fine-tuning frequently outperforms full-rank fine-tuning, and, additionally, that restricting which model blocks are fine-tuned frequently improves results. Together, the results in this thesis provide new insights and techniques for combining trustworthiness and efficiency during neural network inference and training.

},
  author       = {Iofinova, Eugenia B},
  issn         = {2663-337X},
  pages        = {237},
  publisher    = {Institute of Science and Technology Austria},
  title        = {{On the utility and effects of efficiency in artificial neural networks}},
  doi          = {10.15479/AT-ISTA-21854},
  year         = {2026},
}

@article{21982,
  abstract     = {A floating Leidenfrost droplet exhibits curvature inversion of its underside, due to the balance of vapor pressure and surface tension. Using interferometric imaging, we find different behavior for a levitated hydrogel sphere. Curvature inversion is observed briefly just after deposition, but quickly gives way to a steady state with no inversion. We show the essential role of vaporization in shaping the underbelly of the hydrogel, where changes due to direct mass loss are more significant than the balance of vapor pressure and elastic forces.},
  author       = {Diaz Melian, Vicente L and Lenton, Isaac C and Binysh, Jack and Souslov, Anton and Waitukaitis, Scott R},
  issn         = {2470-0053},
  journal      = {Physical Review E},
  number       = {5},
  publisher    = {American Physical Society},
  title        = {{Geometry of the vapor layer under a Leidenfrost hydrogel sphere}},
  doi          = {10.1103/m7gr-2t6j},
  volume       = {113},
  year         = {2026},
}

@phdthesis{23005,
  abstract     = {When a Leidenfrost droplet floats on its own vapor layer, the interplay between vapor pressure, surface tension, and gravity determines its shape, and in the stable regime the underside of the droplet exhibits curvature inversion. Using interferometric imaging, we observe a different behavior for a levitated hydrogel sphere. Curvature inversion appears briefly after deposition, but the continuous vaporization process removes this feature, leading first to an oscillatory regime and eventually to a steady state without curvature inversion. We demonstrate the essential role of vaporization in shaping the hydrogel underbelly, where direct mass loss has a stronger influence than the balance between vapor pressure and elastic forces.},
  author       = {Diaz Melian, Vicente L},
  issn         = {2663-337X},
  pages        = {114},
  publisher    = {Institute of Science and Technology Austria},
  title        = {{The morphology underneath a levitated hydrogel sphere}},
  doi          = {10.15479/AT-ISTA-23005},
  year         = {2026},
}

@phdthesis{22981,
  author       = {Gruber, Nathalie},
  issn         = {2663-337X},
  pages        = {102},
  publisher    = {Institute of Science and Technology Austria},
  title        = {{Genetic strategies enabling bacterial adaptation to selective pressures}},
  doi          = {10.15479/AT-ISTA-22981},
  year         = {2026},
}

@article{21743,
  abstract     = {We present symplectic structures on the shape space of unparameterized space curves that generalize the classical Marsden–Weinstein structure. Our method integrates the Liouville 1-form of the Marsden–Weinstein structure with Riemannian structures that have been introduced in mathematical shape analysis. We also derive Hamiltonian vector fields for several classical Hamiltonian functions with respect to these new symplectic structures.},
  author       = {Bauer, Martin and Ishida, Sadashige and Michor, Peter W.},
  issn         = {1432-1467},
  journal      = {Journal of Nonlinear Science},
  number       = {2},
  publisher    = {Springer Nature},
  title        = {{Symplectic structures on the space of space curves}},
  doi          = {10.1007/s00332-026-10266-8},
  volume       = {36},
  year         = {2026},
}

@article{14703,
  abstract     = {We present a discretization of the dynamic optimal transport problem for which we can obtain the convergence rate for the value of the transport cost to its continuous value when the temporal and spatial stepsize vanish. This convergence result does not require any regularity assumption on the measures, though experiments suggest that the rate is not sharp. Via an analysis of the duality gap we also obtain the convergence rates for the gradient of the optimal potentials and the velocity field under mild regularity assumptions. To obtain such rates we discretize the dual formulation of the dynamic optimal transport problem and use the mature literature related to the error due to discretizing the Hamilton-Jacobi equation.},
  author       = {Ishida, Sadashige and Lavenant, Hugo},
  issn         = {1615-3383},
  journal      = {Foundations of Computational Mathematics},
  keywords     = {Optimal transport, Hamilton-Jacobi equation, convex optimization},
  pages        = {349--384},
  publisher    = {Springer Nature},
  title        = {{Quantitative convergence of a discretization of dynamic optimal transport using the dual formulation}},
  doi          = {10.1007/s10208-024-09686-3},
  volume       = {26},
  year         = {2026},
}

@phdthesis{22804,
  abstract     = {Embryo cleavage — a series of rapid, reductive cell divisions — is the first morphogenetic movement following fertilisation. It lays the foundation for subsequent developmental events, including gastrulation, germ layer specification, organogenesis, and the establishment of the overall body plan. Two major modes of cleavage exist in the animal kingdom: holoblastic (complete) and meroblastic (incomplete) cleavage. Because holoblastic cleavage resembles canonical cytokinesis, its biochemical and mechanical basis has been extensively studied — an annular contractile ring forms at the equator and constricts in a purse-string-like manner, leading to the complete separation of two daughter cells. In contrast, although meroblastic cleavage occurs widely across the animal kingdom (e.g. in fish, reptiles, birds, and cephalopod molluscs), its mechanical basis remains largely unclear. During meroblastic cleavage, the cytokinetic furrow forms only at one pole and does not traverse the entire embryo, raising the question of how cytokinesis proceeds in the absence of a closed contractile ring. Moreover, the resulting daughter cells are not fully separated from the underlying yolk compartment, and how these blastomeres are subsequently cellularised remains unknown. This thesis takes the zebrafish as a model organism to address both questions. The first part characterises the biochemical and mechanical mechanisms underlying non-canonical meroblastic cleavage, revealing a two-phase process in which actomyosin cable contraction and cadherin-mediated membrane adhesion act sequentially to drive furrow ingression and invagination. The second part sheds light on the spatiotemporal dynamics by which individual blastomeres become cellularised, and uncovers a previously unrecognised contribution of central blastomeres to the yolk syncytial layer.},
  author       = {Tong, Xin},
  isbn         = {978-3-99078-080-0},
  issn         = {2663-337X},
  keywords     = {meroblastic cleavage, cytokinesis, active gel theory, embryogenesis, zebrafish, adhesion},
  pages        = {121},
  publisher    = {Institute of Science and Technology Austria},
  title        = {{Towards a deeper understanding of meroblastic cleavage}},
  doi          = {10.15479/AT-ISTA-22804},
  year         = {2026},
}

@misc{22777,
  author       = {Tong, Xin},
  publisher    = {Institute of Science and Technology Austria},
  title        = {{Towards a deeper understanding of meroblastic cleavage - supplementary movies}},
  doi          = {10.15479/AT-ISTA-22777},
  year         = {2026},
}

@article{22967,
  abstract     = {Alkali salts are widely used in solution processing, yet the corresponding cations are often assumed to remain in the liquid phase. Here, we show that alkali ions introduced during the solution synthesis of SnSe are retained through particle isolation and continue to influence the material during subsequent thermal processing, where they shape the evolution of the final polycrystalline material. Different SnSe powders were prepared using Li+, Na+, and K+ precursors, as well as tetramethylammonium (TMA+) precursors as a nonalkali reference for comparison, and all samples were consolidated under identical conditions. Although all three alkali ions were found in the matrix, at grain boundaries, and in segregated nanoscale regions, they partitioned differently and resulted in distinct grain sizes, defect distributions, and therefore transport properties. Li induced the strongest grain size heterogeneity and the lowest energy barriers, Na the best overall balance between carrier concentration and mobility, and K the broadest alkali-rich grain boundary regions along with the strongest interfacial penalty to charge carrier transport. These results show that residual alkali ions are not just remnants of solution synthesis but active determinants of microstructure and thermoelectric performance in SnSe.},
  author       = {Fiedler, Christine and Horta, Sharona and Navita, Navita and Maji, Krishnendu and Kleinhanns, Tobias and Llorca, Jordi and Wang, Qi and Ramon, Maria Garcia and Das, Sambit and Gavini, Vikram and Liu, Yu and Ibáñez, Maria},
  issn         = {1520-5002},
  journal      = {Chemistry of Materials},
  number       = {18},
  pages        = {9323–9332},
  publisher    = {American Chemical Society},
  title        = {{Alkali ions retained from synthesis govern microstructure and transport in solution-processed SnSe}},
  doi          = {10.1021/acs.chemmater.6c01284},
  volume       = {38},
  year         = {2026},
}

@article{22963,
  abstract     = {Although studies of tumor invasion have mainly emphasized the evolution of genetic and epigenetic heterogeneity, cellular behaviors also depend on the physical microenvironment. Yet, the tumor microenvironment is both complex and continuously remodeled, making it hard to rigorously test its causal influence on tumor dissemination. Here, we adopted a reductionist approach to studying tumor cell invasion in microengineered environments of tunable patterned geometries. We find that not only the presence of obstacles but more unexpectedly their spatial disorder causes a drastic shift from a collective to a single-cell mode of invasion—comparable in strength to loss of cell-cell adhesion. Combining live-imaging and perturbation experiments with minimal biophysical modeling, we demonstrate that cell dissemination results both from local geometrical constraints and a global integration of spatial disorder over time. We identify generic universality classes of invasion dynamics dependent on environmental geometry, enabling us to identify quantitative physical principles for tumor dissemination.},
  author       = {Dunajova, Zuzana and Tasciyan, Saren and Majek, Juraj and Merrin, Jack and Jenkins, Robert P. and Sahai, Erik and Sixt, Michael K and Hannezo, Edouard B},
  issn         = {2375-2548},
  journal      = {Science Advances},
  number       = {37},
  publisher    = {AAAS},
  title        = {{Substrate heterogeneity promotes cancer cell dissemination through interface roughening}},
  doi          = {10.1126/sciadv.aed0587},
  volume       = {12},
  year         = {2026},
}

@article{22971,
  abstract     = {We study the problem of minimizing metric distortion in multi-winner elections, where a committee of size k is selected from a set of candidates based on voters’ ordinal preferences. We assume that voters and candidates are embedded on a line metric, and social cost is determined by the underlying metric distances.
The distortion of a voting rule is the worst-case ratio between the social cost of the elected committee and an optimal committee. Previous work has focused on the q-cost model, in which a voter’s cost is given by the distance to their qth closest committee member. Here, we study the additive cost, where a voter’s cost is the sum of distances to all committee members.
We introduce the Polar Comparison Rule and analyze its distortion under utilitarian additive cost. We show that it achieves a distortion upper bound of almost 2.33 for all committee sizes k > 4, improving upon the previously best-known upper bound of 3. Moreover, for k = 2 and k = 3, we establish tight distortion bounds of 2.41 and 2.33, respectively. We also derive lower bounds that depend on the parity of k and analyze the behavior of distortion for small and large committee sizes. Finally, we extend our results to the egalitarian additive cost.},
  author       = {Babashah, Negar and Karimi, Hasti and Seddighin, Masoud and Shahkarami, Golnoosh},
  issn         = {2167-8383},
  journal      = {ACM Transactions on Economics and Computation},
  publisher    = {ACM},
  title        = {{Distortion of multi-winner elections on the line metric: The polar comparison rule}},
  doi          = {10.1145/3843232},
  year         = {2026},
}

@article{22998,
  abstract     = {Balancing selection, a form of selection that maintains genetic diversity, is difficult to detect, and the importance of balancing selection for the maintenance of genetic variation may be larger than often assumed. We model the possibility that the diversity-promoting effects of balancing selection extend to other loci that show sign epistasis with a locus under balancing selection. Rather than focusing on overdominance, as was done in previous efforts, we explore the effects of negative frequency dependence and show that this has important effects on the conditions under which the diversity-promoting effect of epistasis can occur in diploids. Our results show that not only recombination rate but also the dominance of sign epistasis are key parameters that determine the maintenance of polymorphism beyond the locus under direct balancing selection. We suggest that the effect we explore may play a significant role, especially when balancing selection acts on major effect loci.},
  author       = {Khudiakova, Kseniia and Barton, Nicholas H and Arnqvist, Göran},
  issn         = {1096-0325},
  journal      = {Theoretical Population Biology},
  keywords     = {Sign epistasis, Balancing selection, Within-population genetic variation},
  pages        = {48--55},
  title        = {{Sign epistasis extends the effects of balancing selection on genetic diversity}},
  doi          = {10.1016/j.tpb.2026.09.001},
  volume       = {172},
  year         = {2026},
}

@article{23001,
  abstract     = {A famous conjecture by Itai and Zehavi states that, for every 𝑑
-vertex-connected graph 𝐺
 and every vertex 𝑟
 in 𝐺
, there are 𝑑
 spanning trees of 𝐺
 such that, for every vertex 𝑣
 in 𝐺 ∖{𝑟}
, the paths between 𝑟
 and 𝑣
 in different trees are internally vertex-disjoint. We show that with high probability the Itai–Zehavi conjecture holds asymptotically for the Erdős–Rényi random graph 𝐺⁡(𝑛,𝑝)
 when 𝑛⁢𝑝 =𝜔⁡(log⁡𝑛)
 and for random regular graphs 𝐺⁡(𝑛,𝑑)
 when 𝑑 =𝜔⁡(log⁡𝑛)
. Moreover, we essentially confirm the conjecture up to a constant factor for sparser random regular graphs. This answers a question of Draganić and Krivelevich positively. Our proof makes use of recent developments on sprinkling techniques in random regular graphs.},
  author       = {Hollom, Lawrence and Lichev, Lyuben and Mond, Adva and Portier, Julien and Wang, Yiting},
  issn         = {1098-2418},
  journal      = {Random Structures and Algorithms},
  number       = {2},
  publisher    = {Wiley},
  title        = {{Approximate Itai–Zehavi conjecture for random graphs}},
  doi          = {10.1002/rsa.70095},
  volume       = {69},
  year         = {2026},
}

@phdthesis{23033,
  author       = {Stöllner, Andrea},
  issn         = {2663-337X},
  keywords     = {aerosol physics, electrostatics, optics, optical tweezers, atmospheric electricity},
  pages        = {88},
  publisher    = {Institute of Science and Technology Austria},
  title        = {{Microscale electrical behavior of highly charged individual aerosol particles using optical tweezers}},
  doi          = {10.15479/AT-ISTA-23033},
  year         = {2026},
}

@inproceedings{23055,
  abstract     = {We report progress toward strong electric-dipole coupling of polar molecules in cryogenic crystals to superconducting microwave resonators for hybrid quantum computing. We detect crystal-shifted inversion transitions of ammonia in neon using a multimode resonator.},
  author       = {De Zordo, Nikolaus and Borja Espinosa, Carla N and Al Hyder, Ragheed and Li, Jinglun and Kersten, Wenzel and Kanagin, Andrew and Koutentakis, Georgios and Kluibenschedl, Florian and Lemeshko, Mikhail and Fink, Johannes M and Schmiedmayer, Jörg and Redchenko, Elena},
  booktitle    = {Quantum 2.0 Conference and Exhibition},
  isbn         = {9781957171616},
  location     = {Glasgow, United Kingdom},
  publisher    = {Optica Publishing Group},
  title        = {{Detecting polar molecules with superconducting microwave resonators}},
  year         = {2026},
}

@inproceedings{23056,
  abstract     = {Superconducting qubits face scaling challenges due to millikelvin temperature requirements. Here we demonstrate the generation and low-noise upconversion of single microwave photons to telecom frequencies, paving the way for quantum networks with superconducting qubits.},
  author       = {Militaru, Andrei and Werner, Thomas and Riyazi, Erfan and Hawaldar, Samarth and Sahu, Rishabh and Arnold, Georg M and Falthansl-Scheinecker, Paul and Sanchez Naranjo, Jennifer Anais and Loi, Dante and Kapoor, Lucky and Zemlicka, Martin and Qiu, Liu and Fink, Johannes M},
  booktitle    = {Quantum 2.0 Conference and Exhibition},
  isbn         = {9781957171616},
  location     = {Glasgow, United Kingdom},
  publisher    = {Optica Publishing Group},
  title        = {{Electro-optic conversion of itinerant Fock states}},
  year         = {2026},
}