5 papers
Milestoning Markov-jump dynamics: Stationary properties, thermodynamic consistency, kinetic hysteresis, and fluctuation symmetries
Tassilo Schwarz, David Hartich, Aljaž Godec
We derive an exact coarse graining of generic Markov-jump processes into observable semi-Markov dynamics. Exact results for waiting-time distributions for jumps between observable…
Optimal Initialization in Depth: Lyapunov Initialization and Limit Theorems for Deep Leaky ReLU Networks
Constantin Kogler, Tassilo Schwarz, Samuel Kittle
Effective initialization in deep networks requires an understanding of random neural networks. In this work, a rigorous probabilistic analysis of deep bias-free random Leaky ReLU n…
Permutation-Invariant Spectral Learning via Dyson Diffusion
Tassilo Schwarz, Cai Dieball, Constantin Kogler +4
Diffusion models are central to generative modeling and have been adapted to graphs by diffusing adjacency matrix representations. The challenge of having up to such represent…
Consistent time reversal and reliable and accurate inference in the presence of memory
Tassilo Schwarz, Anatoly B. Kolomeisky, Aljaž Godec
Thermodynamic inference from coarse observations remains a key challenge. Memory, in particular correlations between consecutively observed mesostates, blur signatures of irreversi…
Complex-Weighted Convolutional Networks: Provable Expressiveness via Complex Diffusion
Cristina López Amado, Tassilo Schwarz, Yu Tian +1
Graph Neural Networks (GNNs) have achieved remarkable success across diverse applications, yet they remain limited by oversmoothing and poor performance on heterophilic graphs. To…