← Authors

Shengyang Sun

13 papers · 2017–2023 · 5 conferences · across top CS/AI conferences

Achievements

🐣 Hot Topic Early Bird πŸƒ Academic Marathon (6) 🐝 Cross-Pollinator (13) πŸ—ΊοΈ Taxonomy Completionist (20) πŸŒ‰ Interdisciplinary Bridge 🧭 Keyword Pioneer 🌍 Conference Polyglot (5) πŸš€ Conference Pioneer πŸ’Ž Century Club (13) ❓ The Questioner

Conferences

ICLR (5) ICML (4) AISTATS (2) CVPR (1) NIPS (1)

Top co-authors

Roger Grosse (5) Jiaxin Shi (4) Guodong Zhang (3) Chaoqi Wang (2) Jun Zhu (2) Jimmy Ba (1) Wenyuan Zeng (1) David Duvenaud (1) Michalis Titsias (1) Denny Wu (1)

Keywords

variational inference (4) gaussian process (3) uncertainty estimation (2) bayesian neural network (2) bayesian inference (1) scene understanding (1) contrastive learning (1) variational gaussian process (1) video anomaly detection (1) kernel learning (1) gradient estimation (1) kernel approximation (1) posterior distribution (1) video understanding (1) rademacher complexity (1) natural gradient (1) bayesian optimization (1) hamiltonian monte carlo (1) gaussian processes (1) semantic segmentation (1)

Papers

Hierarchical Semantic Contrast for Scene-Aware Video Anomaly Detection CVPR 2023
Understanding the Variance Collapse of SVGD in High Dimensions ICLR 2022
Information-theoretic Online Memory Selection for Continual Learning ICLR 2022
Scalable Variational Gaussian Processes via Harmonic Kernel Decomposition ICML 2021
Beyond Marginal Uncertainty: How Accurately can Bayesian Regression Models Estimate Posterior Predictive Correlations? AISTATS 2021
Aggregated Momentum: Stability Through Passive Damping ICLR 2019
FUNCTIONAL VARIATIONAL BAYESIAN NEURAL NETWORKS ICLR 2019
Fast-rate PAC-Bayes Generalization Bounds via Shifted Rademacher Processes NIPS 2019
Kernel Implicit Variational Inference ICLR 2018
A Spectral Approach to Gradient Estimation for Implicit Distributions ICML 2018
Differentiable Compositional Kernel Learning for Gaussian Processes ICML 2018
Noisy Natural Gradient as Variational Inference ICML 2018
Learning Structured Weight Uncertainty in Bayesian Neural Networks AISTATS 2017