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Ziyu Wang

49 papers · 2012–2026 · 13 conferences · across top CS/AI conferences

Achievements

🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🐝 Cross-Pollinator (13) πŸƒ Academic Marathon (13) 🌍 Conference Polyglot (13) 🌈 Renaissance Researcher (6) πŸŒ‰ Interdisciplinary Bridge πŸ—ΊοΈ Taxonomy Completionist (13) 🀝 Dynamic Duo (11) πŸ‘‘ Triple Crown πŸ† Grand Slam πŸ‘₯ Mega-Team (34) πŸš€ Conference Pioneer ⚑ Prolific Year (8) πŸ”₯ Unstoppable (14) πŸ—ƒοΈ Keyword Collector (202) ❓ The Questioner (2) πŸ’Ž Century Club (48) πŸ“ˆ Trend Setter

Conferences

NIPS (11) ICML (8) ICLR (7) AISTATS (5) CVPR (5) RSS (3) AAAI (2) CORL (2) ICCV (2) ACL (1) ECCV (1) IJCAI (1) UAI (1)

Top co-authors

Nando de Freitas (11) Jun Zhu (7) Nicolas Heess (5) Misha Denil (5) Nando Freitas (5) Alexander Novikov (5) Konrad Zolna (4) Sergio GΓ³mez Colmenarejo (4) Thomas Paine (4) Serkan Cabi (4)

Research topics

Privacy (1)

Keywords

variational autoencoder (4) imitation learning (4) deep reinforcement learning (3) offline reinforcement learning (3) bayesian optimization (3) novel view synthesis (2) instrumental variable regression (2) generative adversarial imitation learning (2) reinforcement learning (2) markov chain monte carlo (2) memory efficiency (2) batch reinforcement learning (2) neural radiance field (2) video generation (2) image generation (2) robotic manipulation (2) policy gradient (2) uncertainty quantification (2) adaptive sampling (2) kernel methods (2)

Papers

Deep Incomplete Multi-View Clustering via Hierarchical Imputation and Alignment AAAI 2026
ArticuBot: Learning Universal Articulated Object Manipulation Policy via Large Scale Simulation RSS 2025
Efficient Fine-Grained Guidance for Diffusion Model Based Symbolic Music Generation ICML 2025
Expert Race: A Flexible Routing Strategy for Scaling Diffusion Transformer with Mixture of Experts ICML 2025
On Probabilistic Truncation in Privacy-preserving Machine Learning AAAI 2025
Synthetic Video Enhances Physical Fidelity in Video Synthesis ICCV 2025
On Subjective Uncertainty Quantification and Calibration in Natural Language Generation AISTATS 2025
Unsupervised Disentanglement of Content and Style via Variance-Invariance Constraints ICLR 2025
Dancing with Still Images: Video Distillation via Static-Dynamic Disentanglement CVPR 2024
Distill Gold from Massive Ores: Bi-level Data Pruning towards Efficient Dataset Distillation ECCV 2024
Flow Snapshot Neurons in Action: Deep Neural Networks Generalize to Biological Motion Perception NIPS 2024
Structured Multi-Track Accompaniment Arrangement via Style Prior Modelling NIPS 2024
DiffTORI: Differentiable Trajectory Optimization for Deep Reinforcement and Imitation Learning NIPS 2024
Is In-Context Learning in Large Language Models Bayesian? A Martingale Perspective ICML 2024
PROC2PDDL: Open-Domain Planning Representations from Texts ACL 2024
Whole-Song Hierarchical Generation of Symbolic Music Using Cascaded Diffusion Models ICLR 2024
HumanGen: Generating Human Radiance Fields With Explicit Priors CVPR 2023
A constrained Bayesian approach to out-of-distribution prediction UAI 2023
Neural Residual Radiance Fields for Streamably Free-Viewpoint Videos CVPR 2023
Object-centric Learning with Cyclic Walks between Parts and Whole NIPS 2023
DynaMixer: A Vision MLP Architecture with Dynamic Mixing ICML 2022
Fast Instrument Learning with Faster Rates NIPS 2022
SWEM: Towards Real-Time Video Object Segmentation With Sequential Weighted Expectation-Maximization CVPR 2022
Kubric: A Scalable Dataset Generator CVPR 2022
Fork or Fail: Cycle-Consistent Training with Many-to-One Mappings AISTATS 2021
Scalable Quasi-Bayesian Inference for Instrumental Variable Regression NIPS 2021
Benchmarks for Deep Off-Policy Evaluation ICLR 2021
Autoregressive Dynamics Models for Offline Policy Evaluation and Optimization ICLR 2021
Task-Relevant Adversarial Imitation Learning CORL 2020
The Usual Suspects? Reassessing Blame for VAE Posterior Collapse ICML 2020
Making Efficient Use of Demonstrations to Solve Hard Exploration Problems ICLR 2020
RL Unplugged: A Suite of Benchmarks for Offline Reinforcement Learning NIPS 2020
Further Analysis of Outlier Detection with Deep Generative Models NIPS 2020
A Wasserstein Minimum Velocity Approach to Learning Unnormalized Models AISTATS 2020
Critic Regularized Regression NIPS 2020
Scaling data-driven robotics with reward sketching and batch reinforcement learning RSS 2020
Function Space Particle Optimization for Bayesian Neural Networks ICLR 2019
Learning an Embedding Space for Transferable Robot Skills ICLR 2018
Playing hard exploration games by watching YouTube NIPS 2018
Reinforcement and Imitation Learning for Diverse Visuomotor Skills RSS 2018
Parallel Multiscale Autoregressive Density Estimation ICML 2017
The Intentional Unintentional Agent: Learning to Solve Many Continuous Control Tasks Simultaneously CORL 2017
Robust Imitation of Diverse Behaviors NIPS 2017
Dueling Network Architectures for Deep Reinforcement Learning ICML 2016
Deep Fried Convnets ICCV 2015
Bayesian Multi-Scale Optimistic Optimization AISTATS 2014
Bayesian Optimization in High Dimensions via Random Embeddings IJCAI 2013
Adaptive Hamiltonian and Riemann Manifold Monte Carlo ICML 2013
Adaptive MCMC with Bayesian Optimization AISTATS 2012