← Optimization & Theory
Machine Learning › Optimization & Theory ›

Stochastic Processes

2667 directly classified papers

Papers per year

Papers

Adaptive Labeling for Efficient Out-of-distribution Model Evaluation NIPS 2024
Neural McKean-Vlasov Processes: Distributional Dependence in Diffusion Processes AISTATS 2024
An Online Bootstrap for Time Series AISTATS 2024
Gradients of Functions of Large Matrices NIPS 2024
Sampling from the Mean-Field Stationary Distribution COLT 2024
Graph Neural Networks Do Not Always Oversmooth NIPS 2024
Improved High-Probability Bounds for the Temporal Difference Learning Algorithm via Exponential Stability COLT 2024
Probabilistic Weather Forecasting with Hierarchical Graph Neural Networks NIPS 2024
First Passage Percolation with Queried Hints AISTATS 2024
TaD: A Plug-and-Play Task-Aware Decoding Method to Better Adapt LLMs on Downstream Tasks IJCAI 2024
The power of an adversary in Glauber dynamics COLT 2024
Intrinsic Gaussian Vector Fields on Manifolds AISTATS 2024
Soft-constrained Schrödinger Bridge: a Stochastic Control Approach AISTATS 2024
Robust variance-regularized risk minimization with concomitant scaling AISTATS 2024
Testing exchangeability by pairwise betting AISTATS 2024
Causal Modeling with Stationary Diffusions AISTATS 2024
Riemannian Laplace Approximation with the Fisher Metric AISTATS 2024
Exact Gradients for Stochastic Spiking Neural Networks Driven by Rough Signals NIPS 2024
A Greedy Approximation for k-Determinantal Point Processes AISTATS 2024
QUEST: Quality-Aware Metropolis-Hastings Sampling for Machine Translation NIPS 2024
Stochastic Approximation with Delayed Updates: Finite-Time Rates under Markovian Sampling AISTATS 2024
Inferring stochastic low-rank recurrent neural networks from neural data NIPS 2024
Measuring Sample Quality in Algorithms for Intractable Normalizing Function Problems JMLR 2024
Errors are Robustly Tamed in Cumulative Knowledge Processes COLT 2024
Blending Data-Driven Priors in Dynamic Games RSS 2024