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Stochastic Processes

2667 directly classified papers

Papers per year

Papers

An Analytic Solution to Covariance Propagation in Neural Networks AISTATS 2024
Balancing Context Length and Mixing Times for Reinforcement Learning at Scale NIPS 2024
Adaptive importance sampling for heavy-tailed distributions via $α$-divergence minimization AISTATS 2024
On Feynman-Kac training of partial Bayesian neural networks AISTATS 2024
Adaptive Exploration for Data-Efficient General Value Function Evaluations NIPS 2024
Probabilistic Calibration by Design for Neural Network Regression AISTATS 2024
From Coupled Oscillators to Graph Neural Networks: Reducing Over-smoothing via a Kuramoto Model-based Approach AISTATS 2024
Action Gaps and Advantages in Continuous-Time Distributional Reinforcement Learning NIPS 2024
Linear Convergence of Black-Box Variational Inference: Should We Stick the Landing? AISTATS 2024
ChaosBench: A Multi-Channel, Physics-Based Benchmark for Subseasonal-to-Seasonal Climate Prediction NIPS 2024
PROMISE: Preconditioned Stochastic Optimization Methods by Incorporating Scalable Curvature Estimates JMLR 2024
Stochastic Optimal Control for Diffusion Bridges in Function Spaces NIPS 2024
Characterizing the Confidence of Large Language Model-Based Automatic Evaluation Metrics EACL 2024
Adam with model exponential moving average is effective for nonconvex optimization NIPS 2024
Approximating Intersections and Differences Between Linear Statistical Shape Models Using Markov Chain Monte Carlo WACV 2024
Parameter Symmetry and Noise Equilibrium of Stochastic Gradient Descent NIPS 2024
Faster Rates of Differentially Private Stochastic Convex Optimization JMLR 2024
Revisiting the Noise Model of Stochastic Gradient Descent AISTATS 2024
Stein Variational Ergodic Search RSS 2024
Self-Supervised 3D Human Mesh Recovery from a Single Image with Uncertainty-Aware Learning AAAI 2024
Why is parameter averaging beneficial in SGD? An objective smoothing perspective AISTATS 2024
Implicit Bias in Noisy-SGD: With Applications to Differentially Private Training AISTATS 2024
An Efficient High-dimensional Gradient Estimator for Stochastic Differential Equations NIPS 2024
Generalization Bounds for Label Noise Stochastic Gradient Descent AISTATS 2024
3D Gaussian Splatting as Markov Chain Monte Carlo NIPS 2024