1. Efficient Exploration in Continuous-time Model-based Reinforcement Learning 

   Treven, Lenart; Hübotter, Jonas; Sukhija, Bhavya; et al. (2023)

   Advances in Neural Information Processing Systems 36

   Reinforcement learning algorithms typically consider discrete-time dynamics, even though the underlying systems are often continuous in time. In this paper, we introduce a model-based reinforcement learning algorithm that represents continuous-time dynamics using nonlinear ordinary differential equations (ODEs). We capture epistemic uncertainty using well-calibrated probabilistic models, and use the optimistic principle for exploration. ...

   Conference Paper

2. Non-commutative perturbation theory for spin dynamics explains the factorization properties of RIDME background 

   Kuzin, Sergei; Yulikov, Maxim; Jeschke, Gunnar (2024)

   Journal of Magnetic Resonance

   The intermolecular hyperfine relaxation-induced dipolar modulation enhancement (ih-RIDME) experiment has a promising potential to quantitatively characterize the nuclear environment in the 0.8-3 nm range around an electron spin. Such information about the spatial arrangement of nuclei is of great interest for structural biology as well as for dynamic nuclear polarization (DNP) methods. In order to develop a reliable and sensitive spectroscopic ...

   Journal Article

3. CLadder: Assessing Causal Reasoning in Language Models 

   Jin, Zhijing; Chen, Yuen; Leeb, Felix; et al.

   Advances in Neural Information Processing Systems 36

   The ability to perform causal reasoning is widely considered a core feature of intelligence. In this work, we investigate whether large language models (LLMs) can coherently reason about causality. Much of the existing work in natural language processing (NLP) focuses on evaluating commonsense causal reasoning in LLMs, thus failing to assess whether a model can perform causal inference in accordance with a set of well-defined formal rules. ...

   Conference Paper

4. PathGES: An Efficient and Secure Graph Encryption Scheme for Shortest Path Queries 

   Falzon, Francesca; Ghosh, Esha; Paterson, Kenneth G.; et al. (2024)

   The increasing importance of graph databases and cloud storage services prompts the study of private queries on graphs. We propose PathGES, a graph encryption scheme (GES) for single-pair shortest path queries. PathGES is efficient and mitigates the state-of-the-art attack by Falzon and Paterson (2022) on the GES by Ghosh, Kamara, and Tamassia (2021), while only incurring an additional logarithmic factor in storage overhead. PathGES ...

   Conference Paper

5. Nonadiabatic Tunneling in Chemical Reactions 

   Richardson, Jeremy O. (2024)

   The Journal of Physical Chemistry Letters

   Quantum tunneling can have a dramatic effect on chemical reaction rates. In nonadiabatic reactions such as electron transfers or spin crossovers, nuclear tunneling effects can be even stronger than for adiabatic proton transfers. Ring-polymer instanton theory enables molecular simulations of tunneling in full dimensionality and has been shown to be far more reliable than commonly used separable approximations. First-principles instanton ...

   Journal Article

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