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Stochastic Processes

438 papers

Papers per year

7
9
29
16
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'15
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'25

Papers

FlowHMM: Flow-based continuous hidden Markov models NIPS 2022
Gold-standard solutions to the Schrödinger equation using deep learning: How much physics do we need? NIPS 2022
Phase transitions in when feedback is useful NIPS 2022
Identification, Amplification and Measurement: A bridge to Gaussian Differential Privacy NIPS 2022
Sampling from Log-Concave Distributions with Infinity-Distance Guarantees NIPS 2022
On the Theoretical Properties of Noise Correlation in Stochastic Optimization NIPS 2022
Efficiency Ordering of Stochastic Gradient Descent NIPS 2022
Reconstruction on Trees and Low-Degree Polynomials NIPS 2022
Trustworthy Monte Carlo NIPS 2022
Multi-fidelity Monte Carlo: a pseudo-marginal approach NIPS 2022
Learning and Covering Sums of Independent Random Variables with Unbounded Support NIPS 2022
High-dimensional limit theorems for SGD: Effective dynamics and critical scaling NIPS 2022
Perfect Sampling from Pairwise Comparisons NIPS 2022
Log-Concave and Multivariate Canonical Noise Distributions for Differential Privacy NIPS 2022
Learning Fractional White Noises in Neural Stochastic Differential Equations NIPS 2022
Re-Analyze Gauss: Bounds for Private Matrix Approximation via Dyson Brownian Motion NIPS 2022
Learning Temporal Point Processes for Efficient Retrieval of Continuous Time Event Sequences AAAI 2022
Conditional Loss and Deep Euler Scheme for Time Series Generation AAAI 2022
Probabilistic Numerical Method of Lines for Time-Dependent Partial Differential Equations AISTATS 2022
A Witness Two-Sample Test AISTATS 2022
Rejection sampling from shape-constrained distributions in sublinear time AISTATS 2022
Sampling from Arbitrary Functions via PSD Models AISTATS 2022
Deep Neyman-Scott Processes AISTATS 2022
Orbital MCMC AISTATS 2022
Adaptation of the Independent Metropolis-Hastings Sampler with Normalizing Flow Proposals AISTATS 2022