@phdthesis{20074, abstract = {Prenatal immune challenges pose significant risks to human embryonic brain and eye development. However, we still lack knowledge about the safe usage of anti-inflammatory drugs during pregnancy. Human induced pluripotent stem cell (hIPSC)-derived brain organoid models provide a unique opportunity to investigate neuronal development and have started to explore functional consequences upon viral infection. However, brain organoids usually lack microglia, the brain-resident immune cells. They are present in the early human embryonic brain and actively participate in neuronal circuit development. At the same time, microglia are known for their immune-sensing properties and will influence viral-mediated effects. In my thesis, I was interested to study the multifunctional role of human microglia during retinal development. In chapter 1, I characterize the innate occurrence of IBA1+-microglia-like cells within the retinal organoid differentiation (Bartalska et al., 2022). Therefore, we differentiate hIPSC using an unguided retinal organoid differentiation protocol and observe the presence of IBA1+-microglia-like cells alongside retinal cups between week 3 and 4 in 2.5D culture. However, instead of infiltrating the neuroectodermal sides, they enrich within non-pigmented, 3D-cystic compartments that develop in low numbers parallel to 3D-retinal organoids. To enrich for IBA1+-microglia precursors (preMG), we guided the differentiation with a low-dosed BMP4 application, which prevents retinal cup development and enhances microglia and 3D-cysts formation. We characterize the differentiated preMG for their microglia-like identity and validated their functionality. In parallel, mass spectrometry identifies the 3D-cysts to express mesenchymal and epithelial markers. We confirm that comparable 3D-cysts are also the preferential environment for IBA1+-microglia-like cells within the unguided retinal organoid differentiation. In chapter 2, I investigate how microglia influence retinal development and whether they contribute to viral-mediated consequences (Schmied et al., 2025). Here, we assemble preMG, which we have characterized in chapter 1, into 3D-retinal organoids. Once the outer plexiform layer forms, microglia-like cells (iMG) populate them and interact with retinal cell types. However, at this developmental stage, the ganglion cell number decreases in 3D-retinal organoids. Thus, we adapted the model into 2D which promotes their survival. Integrated iMG engulf ganglion cells and control their cell number. In parallel, we apply the immunostimulant POLY(I:C) to mimic a fetal viral infection. Although POLY(I:C) stimulation affects iMG phenotype, it does not influence their interaction with ganglion cells. Furthermore, iMG presence significantly contributes to the supernatant’s inflammatory secretome and increases retinal cell proliferation. Simultaneous exposure to the non-steroidal anti-inflammatory drug (NSAID) ibuprofen dampens POLY(I:C)-mediated consequences of the iMG phenotype and ameliorates cell proliferation. Remarkably, while POLY(I:C) disrupts neuronal calcium dynamics independent of iMG presence, ibuprofen rescues this effect only in the presence of iMG. Mechanistically, ibuprofen blocks the enzymes cyclooxygenase 1 and 2 (COX1/ PTGS1 and COX2/ PTGS2) simultaneously, from which iMG predominantly express COX1. Selective inhibition of COX1 does not restore the calcium peak amplitude upon POLY(I:C) stimulation, indicating ibuprofen’s effect depends on the presence and interplay of both, COX1 and COX2. In summary, we characterized the 3D-retinal organoid model for the occurrence of IBA1+-microglia like cells. As the innately developing IBA1+-cells enrich in mesenchymal over retinal structures, we optimized a protocol to differentiate IBA1+-microglia precursors. By combining these two models we generate microglia-assembled retinal organoids. Our results underscore the importance of microglia during neurodevelopment, in the context of prenatal immune challenges and provide insight into the mechanisms by which ibuprofen exerts its protective effects during embryonic development.}, author = {Hübschmann, Verena}, isbn = {978-3-99078-060-2}, issn = {2663-337X}, pages = {151}, publisher = {Institute of Science and Technology Austria}, title = {{Human microglia impact neuronal development in retinal organoids}}, doi = {10.15479/AT-ISTA-20074}, year = {2025}, } @article{20342, abstract = {Safety and liveness stand as fundamental concepts in formal languages, playing a key role in verification. The safety-liveness classification of boolean properties characterizes whether a given property can be falsified by observing a finite prefix of an infinite computation trace (always for safety, never for liveness). In the quantitative setting, properties are arbitrary functions from infinite words to partially-ordered domains. Extending this paradigm to the quantitative domain, where properties are arbitrary functions mapping infinite words to partially-ordered domains, we introduce and study the notions of quantitative safety and liveness. First, we formally define quantitative safety and liveness, and prove that our definitions induce conservative quantitative generalizations of both the safety-progress hierarchy and the safety-liveness decomposition of boolean properties. Consequently, like their boolean counterparts, quantitative properties can be min-decomposed into safety and liveness parts, or alternatively, max-decomposed into co-safety and co-liveness parts. We further establish a connection between quantitative safety and topological continuity and provide alternative characterizations of quantitative safety and liveness in terms of their boolean analogs. Second, we instantiate our framework with the specific classes of quantitative properties expressed by automata. These quantitative automata contain finitely many states and rational-valued transition weights, and their common value functions Inf, Sup, LimInf, LimSup, LimInfAvg, LimSupAvg, and DSum map infinite words into the totally-ordered domain of real numbers. For all common value functions, we provide a procedure for deciding whether a given automaton is safe or live, we show how to construct its safety closure, and we present a min-decomposition into safe and live automata.}, author = {Boker, Udi and Henzinger, Thomas A and Mazzocchi, Nicolas Adrien and Sarac, Naci E}, issn = {1860-5974}, journal = {Logical Methods in Computer Science}, number = {2}, publisher = {EPI Sciences}, title = {{Safety and liveness of quantitative properties and automata}}, doi = {10.46298/lmcs-21(2:2)2025}, volume = {21}, year = {2025}, } @phdthesis{20167, author = {Schön, Hanna}, isbn = {978-3-99078-061-9}, issn = {2663-337X}, pages = {171}, publisher = {Institute of Science and Technology Austria}, title = {{The ER complex SUTU-7/MACO-1 regulates the fate of mRNAs encoding GPCRs}}, doi = {10.15479/AT-ISTA-20167}, year = {2025}, } @article{20538, abstract = {In this study, we describe an integrated approach for methyl group assignment comprising precursor-based selective methyl group labeling, a novel pulse sequence for methyl to backbone coherence transfer and chemical shift predictions using UCBShift 2.0. The utility of this novel α-ketoacid isotopologue is shown by the adaptation of an HMBC-HMQC pulse sequence that simultaneously connects geminal methyl groups of leucine and valine residues to each other and to the protein backbone. By additional 13C,2H-labeling of residues other than valine and leucine residues of the protein, important chemical shift information about neighboring residues (following valine and leucine residues) can be achieved. Thus, different valine and leucine residues in a protein can be characterized as a specific chemical shift vector. Frequency matching with predicted chemical shifts via UCBShift 2.0 using experimental data taken from a subset of the BMRB database revealed a correct assignment performance of about 90%. With applications to proteins of 60.2 kDa and 134 kDa (4 × 33.5 kDa) in size, we demonstrate that the approach provides valuable information even for very large proteins.}, author = {Knödlstorfer, Sonja and Toscano, Giorgia and Ptaszek, Aleksandra L. and Kontaxis, Georg and Napoli, Federico and Schneider, Jakob and Maier, Katharina and Kapitonova, Anna and Lichtenecker, Roman J. and Schanda, Paul and Konrat, Robert}, issn = {1089-8638}, journal = {Journal of Molecular Biology}, number = {23}, publisher = {Elsevier}, title = {{A novel HMBC-CC-HMQC NMR strategy for methyl assignment using triple-13C-labeled α-ketoisovalerate integrated with UCBShift 2.0}}, doi = {10.1016/j.jmb.2025.169465}, volume = {437}, year = {2025}, } @phdthesis{19395, abstract = {Plant growth and development rely significantly on phytohormones, with auxin serving as a master regulator, orchestrating processes from embryogenesis to organogenesis, vascular patterning, and environmental adaptation. Since its conceptual proposition by Charles Darwin in 1880 as an endogenous chemical signal influencing phototropism in grass, auxin has captivated scientists seeking to understand how such a small molecule exerts a profound influence on plant development. One particularly fascinating aspect of auxin function is its ability to self-organize its transport. Through a feedback mechanism between auxin perception and directional transport—primarily mediated by PIN auxin transporters—auxin establishes narrow transport channels. This phenomenon, known as auxin canalization, is fundamental to vascular formation, regeneration, and other key developmental processes. Despite advances in our understanding, driven by experimental studies and computational models, auxin canalization remains an enigma, with many unanswered questions. Like other hormones, auxin functions through intricate signaling pathways. It operates through at least two distinct signaling mechanisms: the well-characterized canonical pathway and the less understood non-canonical pathway. While significant progress has been made in elucidating the canonical pathway, the non-canonical mechanisms remain less defined and require further investigation. In this study, we revisit the non-canonical auxin signaling pathway mediated by the cell-surface complex Auxin Binding Protein 1-Transmembrane Kinase 1 (ABP1-TMK1), with a particular focus on its downstream phosphorylation events. We reveal that this auxin-mediated phosphorylation is conserved across the green lineage, underscoring its fundamental role in plant development. We explore key phosphorylation targets, particularly PIN2, which is essential for root gravitropism. To further understand TMK1’s role in diverse developmental processes, we identified and investigated its interactors as potential co-receptors or regulatory components within its signaling network. Given the previously established role of ABP1-TMK1 in auxin canalization, we sought to further investigate this process and identified several TMK1 interactors also involved in this intricate mechanism. These findings provide new insights into the complex regulation of auxin canalization, highlighting a broader and more interconnected signaling framework than previously understood.}, author = {Monzer, Aline}, issn = {2663-337X}, pages = {160}, publisher = {Institute of Science and Technology Austria}, title = {{Cell-surface auxin signaling: Linking molecular pathways to plant development}}, doi = {10.15479/AT-ISTA-19395}, year = {2025}, } @unpublished{19398, abstract = {Receptor-like kinases (RLKs), particularly the Transmembrane Kinase (TMK) family, play essential roles in signaling and development, with TMKs being key components of auxin perception and downstream phosphorylation events. While TMKs’ involvement in auxin canalization, a process essential for vasculature formation and regeneration, has been established, nonetheless, the additional signaling and regulatory partners remain poorly understood. In this study, we identify and characterize seven leucine-rich repeat RLKs (TINT1–TINT7) as novel interactors of TMK1, revealing their diverse evolutionary, structural, and functional characteristics. Our results show that TINTs interact with TMK1 and highlight their roles in regulating various developmental processes. Majority of TINTs contributes, together with TMK1, to auxin canalization, with TINT5 linking TMK1 to other canalization component CAMEL. Beyond canalization, we also establish the role of TINT-TMK1 interactions in processes such as stomatal movement and the hypocotyl’s gravitropic response. These findings suggest that TINTs, through their interaction with TMK1, are integral components of various signaling networks, contributing to both auxin canalization and broader plant development.}, author = {Monzer, Aline and Mazur, Ewa and Rodriguez Solovey, Lesia and Gallei, Michelle C and Zou, Minxia and Smejkal, Michael and Cervenova, Ema and Friml, Jiří}, booktitle = {bioRxiv}, title = {{TMK interacting network of receptor like kinases for auxin canalization and beyond}}, doi = {10.1101/2025.02.28.640727}, year = {2025}, } @phdthesis{19684, abstract = {The overarching goal of this thesis is to break down the complexity of turbulent flows in terms of enumerable, coherent structures and patterns. In a five-paper series, we adopt a variety of perspectives and techniques to relate the properties of systems of increasing complexity to their underlying coherent structures. Initially, we take a dynamical systems point of view, seeing turbulent flow as a chaotic trajectory bouncing between exact unstable solutions of the underlying equations of motion. Using persistent homology, the main tool of topological data analysis capturing the persistence across scales of topological features in a point cloud, we introduce a method that quantifies visits of turbulent trajectories to unstable time-periodic solutions, also called periodic orbits. We demonstrate this method first in the Rössler and Kuramoto–Sivashinsky systems. Using this method in 3D Kolmogorov flow, we extract a Markov chain from turbulent data, where each node corresponds to the neighbourhood of a periodic orbit. The invariant distribution of this Markov chain reproduces expectation values on turbulent data when it is used to weight averages on the respective periodic orbits. In more realistic, wall-bounded settings, such as plane-Couette flow (pcf) driven by the relative motion of the walls, or plane-Poiseuille flow (ppf) driven by a pressure gradient, finding exact solutions is difficult. We use dynamic mode decomposition (DMD), a dimensionality reduction method for sequential data, to identify and approximate low-dimensional dynamics without knowing any exact solutions. Most spatially-extended systems are equivariant under translations, and in such cases spatial drifts dominate DMD, hindering its use in the search for and modelling of low-dimensional dynamics. We augment DMD with a symmetry reduction method trained on turbulent data to stop it from seeing translations as a feature, improving its ability to extract dynamical information in translation-equivariant systems. We find segments of turbulent trajectories that linearize well with their symmetry-reduced DMD spectra, akin to dynamics near exact solutions. Searching for harmonics in the spectra gives leads for periodic orbits with spatial drifts, one of which converges to a new solution. In larger domains, turbulence can localize and coexist with surrounding laminar flow. Our preceding approaches are global, taking all of a domain into account at once, and cannot readily treat each localized patch individually. Working first in a minimal oblique domain that can host a single 1D-localized turbulent patch, we find that turbulence in ppf is connected to a stable periodic orbit at a flow velocity much lower than when turbulence is first onset. We show that, well in advance of sustained turbulence, chaos sets in explosively, and for long time horizons, time series are consistent with that of a random process. Finally, in much larger domains, we study and compare 2D-localized turbulence that appears as large-scale inclined structures, called stripes, in ppf and pcf. While appearing similar, we find that stripes in these two settings differ significantly in terms of how they sustain themselves, and in higher velocities, how they proliferate.}, author = {Yalniz, Gökhan}, issn = {2663-337X}, pages = {155}, publisher = {Institute of Science and Technology Austria}, title = {{Transition to turbulence: Data-, solution-, and pattern-driven approaches}}, doi = {10.15479/AT-ISTA-19684}, year = {2025}, } @article{19795, abstract = {Super-resolution microscopy often entails long acquisition times of minutes to hours. Since drifts during the acquisition adversely affect data quality, active sample stabilization is commonly used for some of these techniques to reach their full potential. Although drifts in the lateral plane can often be corrected after acquisition, this is not always possible or may come with drawbacks. Therefore, it is appealing to stabilize sample position in three dimensions (3D) during acquisition. Various schemes for active sample stabilization have been demonstrated previously, with some reaching sub-nanometer stability in 3D. Here, we present a scheme for active drift correction that delivers the nanometer-scale 3D stability demanded by state-of-the-art super-resolution techniques and is straightforward to implement compared to previous schemes capable of reaching this level of stabilization precision. Using a refined algorithm that can handle various types of reference structure, without sparse signal peaks being mandatory, we stabilized sample position to ∼1 nm in 3D using objective lenses both with high and low numerical aperture. Our implementation requires only the addition of a simple widefield imaging path and we provide an open-source control software with graphical user interface to facilitate easy adoption of the module. Finally, we demonstrate how this has the potential to enhance data collection for diffraction-limited and super-resolution imaging techniques using single-molecule localization microscopy and cryo-confocal imaging as showcases.}, author = {Vorlaufer, Jakob and Semenov, Nikolai and Kreuzinger, Caroline and Javoor, Manjunath and Zens, Bettina and Agudelo Duenas, Nathalie and Tavakoli, Mojtaba and Suplata, Marek and Jahr, Wiebke and Lyudchik, Julia and Wartak, Andreas and Schur, Florian Km and Danzl, Johann G}, issn = {2667-0747}, journal = {Biophysical Reports}, number = {2}, publisher = {Elsevier}, title = {{Image-based 3D active sample stabilization on the nanometer scale for optical microscopy}}, doi = {10.1016/j.bpr.2025.100211}, volume = {5}, year = {2025}, } @inproceedings{22825, abstract = {The empirical emergence of neural collapse—a surprising symmetry in the feature representations of the training data in the penultimate layer of deep neural networks—has spurred a line of theoretical research aimed at its understanding. However, existing work focuses on data-agnostic models or, when data structure is taken into account, it remains limited to multi-layer perceptrons. Our paper fills both these gaps by analyzing modern architectures in a data-aware regime: we prove that global optima of deep regularized transformers and residual networks (ResNets) with LayerNorm trained with cross entropy or mean squared error loss are approximately collapsed, and the approximation gets tighter as the depth grows. More generally, we formally reduce any end-to-end large-depth ResNet or transformer training into an equivalent unconstrained features model, thus justifying its wide use in the literature even beyond data-agnostic settings. Our theoretical results are supported by experiments on computer vision and language datasets showing that, as the depth grows, neural collapse indeed becomes more prominent.}, author = {Súkeník, Peter and Lampert, Christoph and Mondelli, Marco}, booktitle = {39th Conference on Neural Information Processing Systems}, isbn = {9798331338275}, issn = {1049-5258}, location = {San Diego, CA, United States}, pages = {48646--48677}, publisher = {Neural Information Processing Systems Foundation}, title = {{Neural collapse is globally optimal in deep regularized ResNets and transformers}}, doi = {10.52202/085713-1450}, volume = {38}, year = {2025}, } @inproceedings{22824, abstract = {We present new fast-rate PAC-Bayesian generalization bounds for multi-task and meta-learning in the unbalanced setting, i.e. when the tasks have training sets of different sizes, as is typically the case in real-world scenarios. Previously, only standard-rate bounds were known for this situation, while fast-rate bounds were limited to the setting where all training sets are of equal size. Our new bounds are numerically computable as well as interpretable, and we demonstrate their flexibility in handling a number of cases where they give stronger guarantees than previous bounds. Besides the bounds themselves, we also make conceptual contributions: we demonstrate that the unbalanced multi-task setting has different statistical properties than the balanced situation, specifically that proofs from the balanced situation do not carry over to the unbalanced setting. Additionally, we shed light on the fact that the unbalanced situation allows two meaningful definitions of multi-task risk, depending on whether all tasks should be considered equally important or if sample-rich tasks should receive more weight than samplepoor ones.}, author = {Zakerinia, Hossein and Lampert, Christoph}, booktitle = {39th Conference on Neural Information Processing Systems}, isbn = {9798331338275}, issn = {1049-5258}, location = {San Diego, CA, United States}, pages = {9062--9093}, publisher = {Neural Information Processing Systems Foundation}, title = {{Fast rate bounds for multi-task and meta-learning with different sample sizes}}, doi = {10.52202/085713-0278}, volume = {38}, year = {2025}, } @phdthesis{19903, abstract = {Cooperation, that is, one person paying a cost for another's benefit, is a fundamental principle without which no form of society could exist. The extent to which humans cooperate with each other is also an essential feature that differentiates them from other animals. Cooperation occurs even in the absence of altruistic motivations, when it is selfishly incentivised by the expectation of a future reward. For example, many economic interactions are well described that way. This kind of cooperation requires that people exhibit reciprocal behaviour that acts as a mechanism that rewards cooperation. With game-theoretic models, it is possible to formally study potential such mechanisms and under what conditions they can exist. This thesis contributes to this effort by analysing recently introduced models of cooperation that advance on previous work by taking into account the potential for pre-existing inequality among cooperating individuals as well as the different forms that reciprocity can take. Individuals may differ both intrinsically, in their abilities, as well as extrinsically, in the amount of resources they have available. Allowing for such differences in a model of cooperation helps to understand how inequality affects the potential for, and outcomes of, cooperation among unequals. In this thesis, it is shown that in the presence of intrinsic inequality, a similar unequal distribution of resources can increase the potential for cooperation. This effect is stronger the smaller the group is in which cooperation takes place. It is also shown that under particular assumptions, if the unequal members of a group vary the size of their contributions to a cooperative effort over time, they can thereby increase their efficiency and improve the collective outcome. Cooperative behaviour in a two-person interaction can be rewarded either by direct reciprocation whenever the same two people interact again, or indirectly by a third party who observed the interaction. In the latter case of indirect reciprocity, individuals are proximally rewarded by a good reputation, which ultimately translates to being rewarded with cooperative behaviour by others. This mechanism can enable selfishly motivated cooperation even in circumstances where individuals are unlikely to meet again, akin to how money facilitates trade. While these two forms of reciprocity have mostly been studied in isolation, this thesis analyses both direct and indirect reciprocity in a general model in order to compare their relative effectiveness under different circumstances. The contribution of this thesis is an extension of previous work regarding a specific kind of interaction, whose parameters allow for convenient mathematical analysis, to the most general set of possible interactions.}, author = {Hübner, Valentin}, issn = {2663-337X}, pages = {157}, publisher = {Institute of Science and Technology Austria}, title = {{Reciprocity and inequality in social dilemmas}}, doi = {10.15479/AT-ISTA-19903}, year = {2025}, } @phdthesis{20138, abstract = {The evolution shapes the world around us. Not only in biology, where the fittest individuals spread their genes but also in physics and social dynamics, the evolutionary forces determine the development of a state of matter or public opinions. Many models describe these dynamics. This thesis examines the role of the structure in the models of selection. The population structure is represented as a graph or a network, and each vertex is occupied by one individual. Every individual has a type and fitness that represents the reproductive potential and depends on the type, occupied vertex, and the arrangement of the neighbors. The evolution is modeled in discrete steps; in one step, one individual is replaced by a neighbor selected randomly with the influence of fitness. The role of the networks is widely examined in the literature. The structures that promote the spread of the desired type compared to the structureless case are called amplifiers. The existence of amplifiers in various settings is an intensively studied topic, and in some settings, the amplifiers have been identified. Moreover, there are other important questions about the number of steps until one type spreads over the whole network (fixation time), the computational complexity, and the questions about the robustness of these processes. This thesis explores the role of structure in evolution from many perspectives. First, it introduces different models and various choices that can be made in the models of evolution. It highlights the role of the structure in the real world and how this is reflected in these models. Then, it describes the previous results and open problems. Second, the thesis describes an amplifier for two variants of the Moran process: one with a constant birth rate and the other with a constant death rate. This is an important contribution to the robustness of the amplification. Third, the thesis determines the complexity of spatial games. These are processes where the fitness comes from a game, and the strength of selection is high. It shows that determining the fate of cooperation in these games is a PSPACE-complete problem. Fourth, the thesis describes the amplifier of cooperation for spatial games. This is the first amplifier in this setting. Fifth, the thesis examines the coexistence in the Moran process with environmental heterogeneity. In this setting, the fitness depends not only on the type of the individual but also on the occupied vertex. The chapter determines the relationship between the interactions of vertices of different types and the coexistence time. Sixth, the thesis examines the social balance on networks and proposes a stochastic dynamic partially aware of the state of the graph, which reaches a balanced position quickly. Finally, the thesis presents conclusions and outlines the directions for future work. }, author = {Svoboda, Jakub}, issn = {2663-337X}, pages = {167}, publisher = {Institute of Science and Technology Austria}, title = {{Structural properties of games on graphs}}, doi = {10.15479/AT-ISTA-20138}, year = {2025}, } @inproceedings{20299, abstract = {Deterministic Markov Decision Processes (DMDPs) are a mathematical framework for decision-making where the outcomes and future possible actions are deterministically determined by the current action taken. DMDPs can be viewed as a finite directed weighted graph, where in each step, the controller chooses an outgoing edge. An objective is a measurable function on runs (or infinite trajectories) of the DMDP, and the value for an objective is the maximal cumulative reward (or weight) that the controller can guarantee. We consider the classical mean-payoff (aka limit-average) objective, which is a basic and fundamental objective. Howard's policy iteration algorithm is a popular method for solving DMDPs with mean-payoff objectives. Although Howard's algorithm performs well in practice, as experimental studies suggested, the best known upper bound is exponential and the current known lower bound is as follows: For the input size I, the algorithm requires (math formular) iterations, where (math formular) hides the poly-logarithmic factors, i.e., the current lower bound on iterations is sub-linear with respect to the input size. Our main result is an improved lower bound for this fundamental algorithm where we show that for the input size I, the algorithm requires (math formular) iterations.}, author = {Asadi, Ali and Chatterjee, Krishnendu and De Raaij, Jakob}, booktitle = {The 41st Conference on Uncertainty in Artificial Intelligence}, issn = {2640-3498}, location = {Rio de Janeiro, Brazil}, pages = {223--232}, publisher = {ML Research Press}, title = {{Lower bound on Howard policy iteration for deterministic Markov Decision Processes}}, volume = {286}, year = {2025}, } @inproceedings{20297, abstract = {A standard model that arises in several applications in sequential decision-making is partially observable Markov decision processes (POMDPs) where a decision-making agent interacts with an uncertain environment. A basic objective in POMDPs is the reachability objective, where given a target set of states, the goal is to eventually arrive at one of them. The limit-sure problem asks whether reachability can be ensured with probability arbitrarily close to 1. In general, the limit-sure reachability problem for POMDPs is undecidable. However, in many practical cases, the most relevant question is the existence of policies with a small amount of memory. In this work, we study the limit-sure reachability problem for POMDPs with a fixed amount of memory. We establish that the computational complexity of the problem is NP-complete.}, author = {Asadi, Ali and Chatterjee, Krishnendu and Saona Urmeneta, Raimundo J and Shafiee, Ali}, booktitle = {The 41st Conference on Uncertainty in Artificial Intelligence}, issn = {2640-3498}, location = {Rio de Janeiro, Brazil}, pages = {238--247}, publisher = {ML Research Press}, title = {{Limit-sure reachability for small memory policies in POMDPs is NP-complete}}, volume = {286}, year = {2025}, } @article{20646, abstract = {Describing general quantum many-body dynamics is a challenging task due to the exponential growth of the Hilbert space with system size. The time-dependent variational principle (TDVP) provides a powerful tool to tackle this task by projecting quantum evolution onto a classical dynamical system within a variational manifold. In classical systems, periodic orbits play a crucial role in understanding the structure of the phase space and the long-term behavior of the system. However, finding periodic orbits is generally difficult, and their existence and properties in generic TDVP dynamics over matrix product states have remained largely unexplored. In this work, we develop an algorithm to systematically identify and characterize periodic orbits in TDVP dynamics. Applying our method to the periodically kicked Ising model, we uncover both stable and unstable periodic orbits. We characterize the Kolmogorov-Arnold-Moser tori in the vicinity of stable periodic orbits and track the change of the periodic orbits as we modify the Hamiltonian parameters. We observe that periodic orbits exist at any value of the coupling constant of the kicked Ising model between prethermal and fully thermalizing regimes, but their relevance to quantum dynamics and imprint on quantum eigenstates diminishes as the system leaves the prethermal regime. Our results demonstrate that periodic orbits provide valuable insights into the TDVP approximation of quantum many-body evolution and establish a closer connection between quantum and classical chaos.}, author = {Petrova, Elena and Ljubotina, Marko and Yalniz, Gökhan and Serbyn, Maksym}, issn = {2691-3399}, journal = {PRX Quantum}, number = {4}, publisher = {American Physical Society}, title = {{Finding periodic orbits in projected quantum many-body dynamics}}, doi = {10.1103/tldp-kvkd}, volume = {6}, year = {2025}, } @phdthesis{20607, author = {Mondal, Soumyadip}, isbn = {978-3-99078-071-8}, issn = {2663-337X}, pages = {71}, publisher = {Institute of Science and Technology Austria}, title = {{Oxygen and sulfur redox: Conversion kinetics and phase equilibria}}, doi = {10.15479/AT-ISTA-20607}, year = {2025}, } @inproceedings{22828, abstract = {We propose Joint Moment Estimation (JME), a method for continually and privately estimating both the first and second moments of a data stream with reduced noise compared to naive approaches. JME supports the matrix mechanism and exploits a joint sensitivity analysis to identify a privacy regime in which the second-moment estimation incurs no additional privacy cost, thereby improving accuracy while maintaining privacy. We demonstrate JME’s effectiveness in two applications: estimating the running mean and covariance matrix for Gaussian density estimation and model training with DP-Adam.}, author = {Kalinin, Nikita and Upadhyay, Jalaj and Lampert, Christoph}, booktitle = {Advances in Neural Information Processing Systems}, isbn = {9798331338275}, issn = {1049-5258}, location = {San Diego, CA, United States}, pages = {64002--64047}, publisher = {Neural Information Processing Systems Foundation}, title = {{Continual release moment estimation with differential privacy}}, doi = {10.52202/085713-1924}, volume = {38}, year = {2025}, } @inproceedings{22827, abstract = {Quantized training of Large Language Models (LLMs) remains an open challenge, as maintaining accuracy while performing all matrix multiplications in low precision has proven difficult. This is particularly the case when fine-tuning pre-trained models, which can have large weight, activation, and error (output gradient) outlier values that make lower-precision optimization difficult. To address this, we present HALO, a new quantization-aware training approach for Transformers that enables accurate and efficient low-precision training by combining 1) strategic placement of Hadamard rotations in both forward and backward passes, which mitigate outliers, 2) high-performance kernel support, and 3) FSDP integration for low-precision communication. Our approach ensures that all large matrix multiplications during the forward and backward passes are executed in lower precision. Applied to LLaMa models, HALO achieves near-full-precision-equivalent results during fine-tuning on various tasks, while delivering up to 1.41x end-to-end speedup for full fine-tuning on RTX 4090 GPUs. HALO efficiently supports both standard and parameter-efficient fine-tuning (PEFT). Our results demonstrate the first practical approach to fully quantized LLM fine-tuning that maintains accuracy in INT8 and FP6 precision, while delivering performance benefits.}, author = {Ashkboos, Saleh and Nikdan, Mahdi and Tabesh, Soroush and Lopez Castro, Roberto and Hoefler, Torsten and Alistarh, Dan-Adrian}, booktitle = {39th Conference on Neural Information Processing Systems}, isbn = {9798331338275}, issn = {1049-5258}, location = {San Diego, CA, United States}, pages = {131755--131780}, publisher = {Neural Information Processing Systems Foundation}, title = {{HALO: Hadamard-assisted lower-precision optimization for LLMs}}, doi = {10.52202/085713-3966}, volume = {38}, year = {2025}, } @inproceedings{22832, abstract = {In many scientific experiments, the data annotating cost constraints the pace for testing novel hypotheses. Yet, modern machine learning pipelines offer a promising solution—provided their predictions yield correct conclusions. We focus on Prediction-Powered Causal Inferences (PPCI), i.e., estimating the treatment effect in an unlabeled target experiment, relying on training data with the same outcome annotated but potentially different treatment or effect modifiers. We first show that conditional calibration guarantees valid PPCI at population level. Then, we introduce a sufficient representation constraint transferring validity across experiments, which we propose to enforce in practice in Deconfounded Empirical Risk Minimization, our new model-agnostic training objective. We validate our method on synthetic and real-world scientific data, solving impossible problem instances for Empirical Risk Minimization even with standard invariance constraints. In particular, for the first time, we achieve valid causal inference on a scientific experiment with complex recording and no human annotations, fine-tuning a foundational model on our similar annotated experiment.}, author = {Cadei, Riccardo and Demirel, Ilker and De Bartolomeis, Piersilvio and Lindorfer, Lukas and Cremer, Sylvia and Schmid, Cordelia and Locatello, Francesco}, booktitle = {39th Conference on Neural Information Processing Systems}, isbn = {9798331338275}, issn = {1049-5258}, location = {San Diego, CA, United States}, pages = {82200--82229}, publisher = {Neural Information Processing Systems Foundation}, title = {{Prediction-Powered Causal Inferences}}, doi = {10.52202/085713-2479}, volume = {38}, year = {2025}, } @article{20324, abstract = {We report relaxation oscillations in a one-dimensional array of Josephson junctions, wherein the array dynamically switches between low-current and high-current states. The oscillations are current-voltage dual to those ordinarily observed in single junctions. The current-voltage dual circuit quantitatively accounts for temporal dynamics of the array, including the dependence on biasing conditions. Injection locking of the oscillations results in well-developed current plateaux. A thermal model explains the self-consistent reduction of the superconducting gap due to overheating of the array in the high-current state. Our work suggests that overheating determines the switching from the high-current state to the low-current state.}, author = {Mukhopadhyay, Soham and Lancheros Naranjo, Diego A and Senior, Jorden L and Higginbotham, Andrew P}, issn = {2331-7019}, journal = {Physical Review Applied}, publisher = {American Physical Society}, title = {{Dual relaxation oscillations in a Josephson-junction array}}, doi = {10.1103/qvls-7s3q}, volume = {24}, year = {2025}, }