Molei Tao - RankMe

105 papers A* 20A 4B 1C 2Journal 77Unranked 1

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	A Unified View of Drifting and Score-Based Models. CoRR Chieh-Hsin Lai, Bac Nguyen, Naoki Murata, Yuhta Takida, Toshimitsu Uesaka, Yuki Mitsufuji, Stefano Ermon, Molei Tao
2026	J	`jnl`	Diffusion Model's Generalization Can Be Characterized by Inductive Biases toward a Data-Dependent Ridge Manifold. CoRR Ye He, Yitong Qiu, Molei Tao
2026	J	`jnl`	Discrete Adjoint Schrödinger Bridge Sampler. CoRR Wei Guo, Yuchen Zhu, Xiaochen Du, Juno Nam, Yongxin Chen, Rafael Gómez-Bombarelli, Guan-Horng Liu, Molei Tao, Jaemoo Choi
2026	J	`jnl`	How Does the ReLU Activation Affect the Implicit Bias of Gradient Descent on High-dimensional Neural Network Regression? CoRR Kuo-Wei Lai, Guanghui Wang, Molei Tao, Vidya Muthukumar
2026	J	`jnl`	LaViDa-R1: Advancing Reasoning for Unified Multimodal Diffusion Language Models. CoRR Shufan Li, Yuchen Zhu, Jiuxiang Gu, Kangning Liu, Zhe Lin, Yongxin Chen, Molei Tao, Aditya Grover, Jason Kuen
2026	J	`jnl`	Prism: Efficient Test-Time Scaling via Hierarchical Search and Self-Verification for Discrete Diffusion Language Models. CoRR Jinbin Bai, Yixuan Li, Yuchen Zhu, Yi Xin, Qingyu Shi, Aosong Feng, Xiaohong Liu, Molei Tao, Jianru Xue, Xiangtai Li, Ming-Hsuan Yang
2026	J	`jnl`	Rethinking the Design Space of Reinforcement Learning for Diffusion Models: On the Importance of Likelihood Estimation Beyond Loss Design. CoRR Jaemoo Choi, Yuchen Zhu, Wei Guo, Petr Molodyk, Bo Yuan, Jinbin Bai, Yi Xin, Molei Tao, Yongxin Chen
2025	J	`jnl`	A Closer Look at Model Collapse: From a Generalization-to-Memorization Perspective. CoRR Lianghe Shi, Meng Wu, Huijie Zhang, Zekai Zhang, Molei Tao, Qing Qu
2025	J	`jnl`	AlignFlow: Improving Flow-based Generative Models with Semi-Discrete Optimal Transport. CoRR Lingkai Kong, Molei Tao, Yang Liu, Bryan Wang, Jinmiao Fu, Chien-Chih Wang, Huidong Liu
2025	J	`jnl`	Appropriate State-Dependent Friction Coefficient Accelerates Kinetic Langevin Dynamics. SIAM J. Appl. Math. Keunwoo Lim, Molei Tao
2025	J	`jnl`	Complexity Analysis of Normalizing Constant Estimation: from Jarzynski Equality to Annealed Importance Sampling and beyond. CoRR Wei Guo, Molei Tao, Yongxin Chen
2025	A*	`conf`	Diffuse Everything: Multimodal Diffusion Models on Arbitrary State Spaces. ICML Kevin Rojas, Yuchen Zhu, Sichen Zhu, Felix X.-F. Ye, Molei Tao
2025	J	`jnl`	Diffuse Everything: Multimodal Diffusion Models on Arbitrary State Spaces. CoRR Kevin Rojas, Yuchen Zhu, Sichen Zhu, Felix X.-F. Ye, Molei Tao
2025	A*	`conf`	Diffusion Generative Modeling for Spatially Resolved Gene Expression Inference from Histology Images. ICLR Sichen Zhu, Yuchen Zhu, Molei Tao, Peng Qiu
2025	J	`jnl`	Diffusion Generative Modeling for Spatially Resolved Gene Expression Inference from Histology Images. CoRR Sichen Zhu, Yuchen Zhu, Molei Tao, Peng Qiu
2025	J	`jnl`	Enhancing Reasoning for Diffusion LLMs via Distribution Matching Policy Optimization. CoRR Yuchen Zhu, Wei Guo, Jaemoo Choi, Petr Molodyk, Bo Yuan, Molei Tao, Yongxin Chen
2025	J	`jnl`	Fast Non-Log-Concave Sampling under Nonconvex Equality and Inequality Constraints with Landing. CoRR Kijung Jeon, Michael Muehlebach, Molei Tao
2025	J	`jnl`	Fast Solvers for Discrete Diffusion Models: Theory and Applications of High-Order Algorithms. CoRR Yinuo Ren, Haoxuan Chen, Yuchen Zhu, Wei Guo, Yongxin Chen, Grant M. Rotskoff, Molei Tao, Lexing Ying
2025	J	`jnl`	From Masks to Worlds: A Hitchhiker's Guide to World Models. CoRR Jinbin Bai, Yu Lei, Hecong Wu, Yuchen Zhu, Shufan Li, Yi Xin, Xiangtai Li, Molei Tao, Aditya Grover, Ming-Hsuan Yang
2025	J	`jnl`	Generalization of Diffusion Models Arises with a Balanced Representation Space. CoRR Zekai Zhang, Xiao Li, Xiang Li, Lianghe Shi, Meng Wu, Molei Tao, Qing Qu
2025	J	`jnl`	Good regularity creates large learning rate implicit biases: edge of stability, balancing, and catapult. J. Mach. Learn. Res. Yuqing Wang, Zhenghao Xu, Tuo Zhao, Molei Tao
2025	J	`jnl`	Improving Reasoning for Diffusion Language Models via Group Diffusion Policy Optimization. CoRR Kevin Rojas, Jiahe Lin, Kashif Rasul, Anderson Schneider, Yuriy Nevmyvaka, Molei Tao, Wei Deng
2025	J	`jnl`	MDNS: Masked Diffusion Neural Sampler via Stochastic Optimal Control. CoRR Yuchen Zhu, Wei Guo, Jaemoo Choi, Guan-Horng Liu, Yongxin Chen, Molei Tao
2025	J	`jnl`	Non-equilibrium Annealed Adjoint Sampler. CoRR Jaemoo Choi, Yongxin Chen, Molei Tao, Guan-Horng Liu
2025	A*	`conf`	Provable Benefit of Annealed Langevin Monte Carlo for Non-log-concave Sampling. ICLR Wei Guo, Molei Tao, Yongxin Chen
2025	J	`jnl`	Provable Separations between Memorization and Generalization in Diffusion Models. CoRR Zeqi Ye, Qijie Zhu, Molei Tao, Minshuo Chen
2025	J	`jnl`	Proximal Diffusion Neural Sampler. CoRR Wei Guo, Jaemoo Choi, Yuchen Zhu, Molei Tao, Yongxin Chen
2025	J	`jnl`	Robust First- and Second-Order Differentiation for Regularized Optimal Transport. SIAM J. Sci. Comput. Xingjie Li, Fei Lu, Molei Tao, Felix X.-F. Ye
2025	A	`conf`	SODA: Spectral Orthogonal Decomposition Adaptation for Diffusion Models. WACV Xinxi Zhang, Song Wen, Ligong Han, Felix Juefei-Xu, Akash Srivastava, Junzhou Huang, Vladimir Pavlovic, Hao Wang, Molei Tao, Dimitris N. Metaxas
2025	J	`jnl`	TR2-D2: Tree Search Guided Trajectory-Aware Fine-Tuning for Discrete Diffusion. CoRR Sophia Tang, Yuchen Zhu, Molei Tao, Pranam Chatterjee
2025	J	`jnl`	Theory-Informed Improvements to Classifier-Free Guidance for Discrete Diffusion Models. CoRR Kevin Rojas, Ye He, Chieh-Hsin Lai, Yuhta Takida, Yuki Mitsufuji, Molei Tao
2025	A*	`conf`	Trivialized Momentum Facilitates Diffusion Generative Modeling on Lie Groups. ICLR Yuchen Zhu, Tianrong Chen, Lingkai Kong, Evangelos A. Theodorou, Molei Tao
2025	J	`jnl`	Variational Learning Finds Flatter Solutions at the Edge of Stability. CoRR Avrajit Ghosh, Bai Cong, Rio Yokota, Saiprasad Ravishankar, Rongrong Wang, Molei Tao, Mohammad Emtiyaz Khan, Thomas Möllenhoff
2025	A	`conf`	Variational Schrödinger Momentum Diffusion. AISTATS Kevin Rojas, Yixin Tan, Molei Tao, Yuriy Nevmyvaka, Wei Deng
2025	J	`jnl`	Variational Schrödinger Momentum Diffusion. CoRR Kevin Rojas, Yixin Tan, Molei Tao, Yuriy Nevmyvaka, Wei Deng
2025	J	`jnl`	What Exactly Does Guidance Do in Masked Discrete Diffusion Models. CoRR Ye He, Kevin Rojas, Molei Tao
2024	J	`jnl`	Automated construction of effective potential via algorithmic implicit bias. CoRR Xingjie Helen Li, Molei Tao
2024	J	`jnl`	Automated construction of effective potential via algorithmic implicit bias. J. Comput. Phys. Xingjie Helen Li, Molei Tao
2024	A*	`conf`	Convergence of Kinetic Langevin Monte Carlo on Lie groups. COLT Lingkai Kong, Molei Tao
2024	J	`jnl`	Convergence of Kinetic Langevin Monte Carlo on Lie groups. CoRR Lingkai Kong, Molei Tao
2024	J	`jnl`	DFU: scale-robust diffusion model for zero-shot super-resolution image generation. CoRR Alexander Havrilla, Kevin Rojas, Wenjing Liao, Molei Tao
2024	J	`jnl`	DeepTTV: Deep Learning Prediction of Hidden Exoplanet From Transit Timing Variations. CoRR Chen Chen, Lingkai Kong, Gongjie Li, Molei Tao
2024	A*	`conf`	Evaluating the design space of diffusion-based generative models. NeurIPS Yuqing Wang, Ye He, Molei Tao
2024	J	`jnl`	Evaluating the design space of diffusion-based generative models. CoRR Yuqing Wang, Ye He, Molei Tao
2024	A	`conf`	Extragradient Type Methods for Riemannian Variational Inequality Problems. AISTATS Zihao Hu, Guanghui Wang, Xi Wang, Andre Wibisono, Jacob D. Abernethy, Molei Tao
2024	J	`jnl`	Generative modeling assisted simulation of measurement-altered quantum criticality. CoRR Yuchen Zhu, Molei Tao, Yuebo Jin, Xie Chen
2024	J	`jnl`	Plug-and-Play Controllable Generation for Discrete Masked Models. CoRR Wei Guo, Yuchen Zhu, Molei Tao, Yongxin Chen
2024	A*	`conf`	Provable Acceleration of Nesterov's Accelerated Gradient for Asymmetric Matrix Factorization and Linear Neural Networks. NeurIPS Zhenghao Xu, Yuqing Wang, Tuo Zhao, Rachel Ward, Molei Tao
2024	J	`jnl`	Provable Acceleration of Nesterov's Accelerated Gradient for Rectangular Matrix Factorization and Linear Neural Networks. CoRR Zhenghao Xu, Yuqing Wang, Tuo Zhao, Rachel Ward, Molei Tao
2024	J	`jnl`	Provable Benefit of Annealed Langevin Monte Carlo for Non-log-concave Sampling. CoRR Wei Guo, Molei Tao, Yongxin Chen
2024	A*	`conf`	Quantitative Convergences of Lie Group Momentum Optimizers. NeurIPS Lingkai Kong, Molei Tao
2024	J	`jnl`	Quantitative Convergences of Lie Group Momentum Optimizers. CoRR Lingkai Kong, Molei Tao
2024	J	`jnl`	Quantum State Generation with Structure-Preserving Diffusion Model. CoRR Yuchen Zhu, Tianrong Chen, Evangelos A. Theodorou, Xie Chen, Molei Tao
2024	J	`jnl`	Robust First and Second-Order Differentiation for Regularized Optimal Transport. CoRR Xingjie Li, Fei Lu, Molei Tao, Felix X.-F. Ye
2024	J	`jnl`	Spectrum-Aware Parameter Efficient Fine-Tuning for Diffusion Models. CoRR Xinxi Zhang, Song Wen, Ligong Han, Felix Juefei-Xu, Akash Srivastava, Junzhou Huang, Hao Wang, Molei Tao, Dimitris N. Metaxas
2024	J	`jnl`	Trivialized Momentum Facilitates Diffusion Generative Modeling on Lie Groups. CoRR Yuchen Zhu, Tianrong Chen, Lingkai Kong, Evangelos A. Theodorou, Molei Tao
2024	A*	`conf`	Zeroth-Order Sampling Methods for Non-Log-Concave Distributions: Alleviating Metastability by Denoising Diffusion. NeurIPS Ye He, Kevin Rojas, Molei Tao
2024	J	`jnl`	Zeroth-Order Sampling Methods for Non-Log-Concave Distributions: Alleviating Metastability by Denoising Diffusion. CoRR Ye He, Kevin Rojas, Molei Tao
2023	A*	`conf`	Deep Momentum Multi-Marginal Schrödinger Bridge. NeurIPS Tianrong Chen, Guan-Horng Liu, Molei Tao, Evangelos A. Theodorou
2023	J	`jnl`	Deep Momentum Multi-Marginal Schrödinger Bridge. CoRR Tianrong Chen, Guan-Horng Liu, Molei Tao, Evangelos A. Theodorou
2023	J	`jnl`	Extragradient Type Methods for Riemannian Variational Inequality Problems. CoRR Zihao Hu, Guanghui Wang, Xi Wang, Andre Wibisono, Jacob D. Abernethy, Molei Tao
2023	J	`jnl`	Good regularity creates large learning rate implicit biases: edge of stability, balancing, and catapult. CoRR Yuqing Wang, Zhenghao Xu, Tuo Zhao, Molei Tao
2023	J	`jnl`	Markov Chain Monte Carlo for Gaussian: A Linear Control Perspective. IEEE Control. Syst. Lett. Bo Yuan, Jiaojiao Fan, Yuqing Wang, Molei Tao, Yongxin Chen
2023	A*	`conf`	Mirror Diffusion Models for Constrained and Watermarked Generation. NeurIPS Guan-Horng Liu, Tianrong Chen, Evangelos A. Theodorou, Molei Tao
2023	J	`jnl`	Mirror Diffusion Models for Constrained and Watermarked Generation. CoRR Guan-Horng Liu, Tianrong Chen, Evangelos A. Theodorou, Molei Tao
2023	A*	`conf`	Momentum Stiefel Optimizer, with Applications to Suitably-Orthogonal Attention, and Optimal Transport. ICLR Lingkai Kong, Yuqing Wang, Molei Tao
2023	J	`jnl`	NySALT: Nyström-type inference-based schemes adaptive to large time-stepping. J. Comput. Phys. Xingjie Li, Fei Lu, Molei Tao, Felix X.-F. Ye
2023	A*	`conf`	gDDIM: Generalized denoising diffusion implicit models. ICLR Qinsheng Zhang, Molei Tao, Yongxin Chen
2022	J	`jnl`	Accurate and efficient simulations of Hamiltonian mechanical systems with discontinuous potentials. J. Comput. Phys. Molei Tao, Shi Jin
2022	A*	`conf`	Alternating Mirror Descent for Constrained Min-Max Games. NeurIPS Andre Wibisono, Molei Tao, Georgios Piliouras
2022	J	`jnl`	Alternating Mirror Descent for Constrained Min-Max Games. CoRR Andre Wibisono, Molei Tao, Georgios Piliouras
2022	J	`jnl`	Data-driven discovery of non-Newtonian astronomy via learning non-Euclidean Hamiltonian. CoRR Oswin So, Gongjie Li, Evangelos A. Theodorou, Molei Tao
2022	A*	`conf`	Hessian-Free High-Resolution Nesterov Acceleration For Sampling. ICML Ruilin Li, Hongyuan Zha, Molei Tao
2022	A*	`conf`	Large Learning Rate Tames Homogeneity: Convergence and Balancing Effect. ICLR Yuqing Wang, Minshuo Chen, Tuo Zhao, Molei Tao
2022	J	`jnl`	Momentum Stiefel Optimizer, with Applications to Suitably-Orthogonal Attention, and Optimal Transport. CoRR Lingkai Kong, Yuqing Wang, Molei Tao
2022	J	`jnl`	NySALT: Nyström-type inference-based schemes adaptive to large time-stepping. CoRR Xingjie Li, Fei Lu, Molei Tao, Felix X.-F. Ye
2022	J	`jnl`	Parametric Resonance for Enhancing the Rate of Metastable Transition. SIAM J. Appl. Math. Ying Chao, Molei Tao
2022	A*	`conf`	Sqrt(d) Dimension Dependence of Langevin Monte Carlo. ICLR Ruilin Li, Hongyuan Zha, Molei Tao
2022	B	`conf`	The Mirror Langevin Algorithm Converges with Vanishing Bias. ALT Ruilin Li, Molei Tao, Santosh S. Vempala, Andre Wibisono
2022	J	`jnl`	gDDIM: Generalized denoising diffusion implicit models. CoRR Qinsheng Zhang, Molei Tao, Yongxin Chen
2021	J	`jnl`	A Derivative-Free Optimization Method With Application to Functions With Exploding and Vanishing Gradients. IEEE Control. Syst. Lett. Said Al-Abri, Tony X. Lin, Molei Tao, Fumin Zhang
2021	J	`jnl`	Accurate and Efficient Simulations of Hamiltonian Mechanical Systems with Discontinuous Potentials. CoRR Molei Tao, Shi Jin
2021	A*	`conf`	Data-driven Prediction of General Hamiltonian Dynamics via Learning Exactly-Symplectic Maps. ICML Renyi Chen, Molei Tao
2021	J	`jnl`	Data-driven Prediction of General Hamiltonian Dynamics via Learning Exactly-Symplectic Maps. CoRR Renyi Chen, Molei Tao
2021	J	`jnl`	Large Learning Rate Tames Homogeneity: Convergence and Balancing Effect. CoRR Yuqing Wang, Minshuo Chen, Tuo Zhao, Molei Tao
2021	J	`jnl`	Sqrt(d) Dimension Dependence of Langevin Monte Carlo. CoRR Ruilin Li, Hongyuan Zha, Molei Tao
2021	J	`jnl`	The Mirror Langevin Algorithm Converges with Vanishing Bias. CoRR Ruilin Li, Molei Tao, Santosh S. Vempala, Andre Wibisono
2021	—	`conf`	Variational Symplectic Accelerated Optimization on Lie Groups. CDC Taeyoung Lee, Molei Tao, Melvin Leok
2020	J	`jnl`	AhKin: A modular and efficient code for the Doppler shift attenuation method. Comput. Phys. Commun. Alejandro Garzón, Wilmar Rodriguez, Fernando Cristancho, Molei Tao
2020	J	`jnl`	Hessian-Free High-Resolution Nesterov Acceleration for Sampling. CoRR Ruilin Li, Hongyuan Zha, Molei Tao
2020	J	`jnl`	Improving Sampling Accuracy of Stochastic Gradient MCMC Methods via Non-uniform Subsampling of Gradients. CoRR Ruilin Li, Xin Wang, Hongyuan Zha, Molei Tao
2020	A*	`conf`	Stochasticity of Deterministic Gradient Descent: Large Learning Rate for Multiscale Objective Function. NeurIPS Lingkai Kong, Molei Tao
2020	J	`jnl`	Stochasticity of Deterministic Gradient Descent: Large Learning Rate for Multiscale Objective Function. CoRR Lingkai Kong, Molei Tao
2020	A	`conf`	Variational Optimization on Lie Groups, with Examples of Leading (Generalized) Eigenvalue Problems. AISTATS Molei Tao, Tomoki Ohsawa
2020	J	`jnl`	Variational Optimization on Lie Groups, with Examples of Leading (Generalized) Eigenvalue Problems. CoRR Molei Tao, Tomoki Ohsawa
2020	A*	`conf`	Why Do Deep Residual Networks Generalize Better than Deep Feedforward Networks? - A Neural Tangent Kernel Perspective. NeurIPS Kaixuan Huang, Yuqing Wang, Molei Tao, Tuo Zhao
2020	J	`jnl`	Why Do Deep Residual Networks Generalize Better than Deep Feedforward Networks? - A Neural Tangent Kernel Perspective. CoRR Kaixuan Huang, Yuqing Wang, Molei Tao, Tuo Zhao
2019	J	`jnl`	Data-driven multiscale decompositions for forecasting and model discovery. CoRR Daniel Dylewsky, Molei Tao, J. Nathan Kutz
2019	C	`conf`	Parametric Resonant Control of Macroscopic Behaviors of Multiple Oscillators. ACC Pengcheng Xie, Molei Tao
2019	J	`jnl`	Simply improved averaging for coupled oscillators and weakly nonlinear waves. Commun. Nonlinear Sci. Numer. Simul. Molei Tao
2016	J	`jnl`	Explicit high-order symplectic integrators for charged particles in general electromagnetic fields. J. Comput. Phys. Molei Tao
2015	J	`jnl`	Convex Optimal Uncertainty Quantification. SIAM J. Optim. Shuo Han, Molei Tao, Ufuk Topcu, Houman Owhadi, Richard M. Murray
2013	C	`conf`	Convex optimal uncertainty quantification: Algorithms and a case study in energy storage placement for power grids. ACC Shuo Han, Ufuk Topcu, Molei Tao, Houman Owhadi, Richard M. Murray
2013	J	`jnl`	Variational integrators for electric circuits. J. Comput. Phys. Sina Ober-Blöbaum, Molei Tao, Mulin Cheng, Houman Owhadi, Jerrold E. Marsden
2010	J	`jnl`	Nonintrusive and Structure Preserving Multiscale Integration of Stiff ODEs, SDEs, and Hamiltonian Systems with Hidden Slow Dynamics via Flow Averaging. Multiscale Model. Simul. Molei Tao, Houman Owhadi, Jerrold E. Marsden