Luhuan Wu - RankMe

17 papers A* 3A 3Journal 9Unranked 2

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Robust Inference-Time Steering of Protein Diffusion Models via Embedding Optimization. CoRR Minhuan Li, Jiequn Han, Pilar Cossio, Luhuan Wu
2025	J	`jnl`	Bayesian Invariance Modeling of Multi-Environment Data. CoRR Luhuan Wu, Mingzhang Yin, Yixin Wang, John P. Cunningham, David M. Blei
2024	A	`conf`	Posterior Uncertainty Quantification in Neural Networks using Data Augmentation. AISTATS Luhuan Wu, Sinead A. Williamson
2024	J	`jnl`	Posterior Uncertainty Quantification in Neural Networks using Data Augmentation. CoRR Luhuan Wu, Sinead Williamson
2023	A*	`conf`	Practical and Asymptotically Exact Conditional Sampling in Diffusion Models. NeurIPS Luhuan Wu, Brian L. Trippe, Christian A. Naesseth, David M. Blei, John P. Cunningham
2023	J	`jnl`	Practical and Asymptotically Exact Conditional Sampling in Diffusion Models. CoRR Luhuan Wu, Brian L. Trippe, Christian A. Naesseth, David M. Blei, John P. Cunningham
2022	—	`conf`	Denoising Deep Generative Models. ICBINB Gabriel Loaiza-Ganem, Brendan Leigh Ross, Luhuan Wu, John P. Cunningham, Jesse C. Cresswell, Anthony L. Caterini
2022	J	`jnl`	Denoising Deep Generative Models. CoRR Gabriel Loaiza-Ganem, Brendan Leigh Ross, Luhuan Wu, John P. Cunningham, Jesse C. Cresswell, Anthony L. Caterini
2022	J	`jnl`	Variational Nearest Neighbor Gaussian Processes. CoRR Luhuan Wu, Geoff Pleiss, John P. Cunningham
2022	A*	`conf`	Variational nearest neighbor Gaussian process. ICML Luhuan Wu, Geoff Pleiss, John P. Cunningham
2021	A*	`conf`	Bias-Free Scalable Gaussian Processes via Randomized Truncations. ICML Andres Potapczynski, Luhuan Wu, Dan Biderman, Geoff Pleiss, John P. Cunningham
2021	J	`jnl`	Bias-Free Scalable Gaussian Processes via Randomized Truncations. CoRR Andres Potapczynski, Luhuan Wu, Dan Biderman, Geoff Pleiss, John P. Cunningham
2021	J	`jnl`	Hierarchical Inducing Point Gaussian Process for Inter-domain Observations. CoRR Luhuan Wu, Andrew Miller, Lauren Anderson, Geoff Pleiss, David M. Blei, John P. Cunningham
2021	A	`conf`	Hierarchical Inducing Point Gaussian Process for Inter-domian Observations. AISTATS Luhuan Wu, Andrew Miller, Lauren Anderson, Geoff Pleiss, David M. Blei, John P. Cunningham
2020	A	`conf`	Variational Objectives for Markovian Dynamics with Backward Simulation. ECAI Antonio Khalil Moretti, Zizhao Wang, Luhuan Wu, Iddo Drori, Itsik Pe'er
2019	J	`jnl`	Particle Smoothing Variational Objectives. CoRR Antonio Khalil Moretti, Zizhao Wang, Luhuan Wu, Iddo Drori, Itsik Pe'er
2019	—	`conf`	Smoothing Nonlinear Variational Objectives with Sequential Monte Carlo. DGS@ICLR Antonio Khalil Moretti, Zizhao Wang, Luhuan Wu, Itsik Pe'er