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Molei Tao

Orcid: 0000-0002-3308-6176

According to our database¹, Molei Tao authored at least 45 papers between 2010 and 2024.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of three.

Timeline

Legend:

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In proceedings

Article

PhD thesis

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Links

On csauthors.net:

Bibliography

2024

Automated construction of effective potential via algorithmic implicit bias.

[BibT_eX]

[DOI]

Xingjie Helen Li

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J. Comput. Phys., 2024

Plug-and-Play Controllable Generation for Discrete Masked Models.

[BibT_eX]

[DOI]

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CoRR, 2024

DeepTTV: Deep Learning Prediction of Hidden Exoplanet From Transit Timing Variations.

[BibT_eX]

[DOI]

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CoRR, 2024

Provable Benefit of Annealed Langevin Monte Carlo for Non-log-concave Sampling.

[BibT_eX]

[DOI]

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CoRR, 2024

Robust First and Second-Order Differentiation for Regularized Optimal Transport.

[BibT_eX]

[DOI]

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CoRR, 2024

Evaluating the design space of diffusion-based generative models.

[BibT_eX]

[DOI]

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CoRR, 2024

Spectrum-Aware Parameter Efficient Fine-Tuning for Diffusion Models.

[BibT_eX]

[DOI]

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Felix Juefei-Xu

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Akash Srivastava

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Dimitris N. Metaxas

CoRR, 2024

Quantitative Convergences of Lie Group Momentum Optimizers.

[BibT_eX]

[DOI]

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CoRR, 2024

Trivialized Momentum Facilitates Diffusion Generative Modeling on Lie Groups.

[BibT_eX]

[DOI]

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Evangelos A. Theodorou

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CoRR, 2024

Quantum State Generation with Structure-Preserving Diffusion Model.

[BibT_eX]

[DOI]

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Evangelos A. Theodorou

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CoRR, 2024

Zeroth-Order Sampling Methods for Non-Log-Concave Distributions: Alleviating Metastability by Denoising Diffusion.

[BibT_eX]

[DOI]

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CoRR, 2024

DFU: scale-robust diffusion model for zero-shot super-resolution image generation.

[BibT_eX]

[DOI]

Alexander Havrilla

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CoRR, 2024

Convergence of Kinetic Langevin Monte Carlo on Lie groups.

[BibT_eX]

[DOI]

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Proceedings of the Thirty Seventh Annual Conference on Learning Theory, June 30, 2024

Extragradient Type Methods for Riemannian Variational Inequality Problems.

[BibT_eX]

[DOI]

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Jacob D. Abernethy

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Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023

NySALT: Nyström-type inference-based schemes adaptive to large time-stepping.

[BibT_eX]

[DOI]

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J. Comput. Phys., March, 2023

Markov Chain Monte Carlo for Gaussian: A Linear Control Perspective.

[BibT_eX]

[DOI]

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IEEE Control. Syst. Lett., 2023

Good regularity creates large learning rate implicit biases: edge of stability, balancing, and catapult.

[BibT_eX]

[DOI]

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CoRR, 2023

Mirror Diffusion Models for Constrained and Watermarked Generation.

[BibT_eX]

[DOI]

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Evangelos A. Theodorou

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Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Deep Momentum Multi-Marginal Schrödinger Bridge.

[BibT_eX]

[DOI]

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Evangelos A. Theodorou

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

gDDIM: Generalized denoising diffusion implicit models.

[BibT_eX]

[DOI]

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Proceedings of the Eleventh International Conference on Learning Representations, 2023

Momentum Stiefel Optimizer, with Applications to Suitably-Orthogonal Attention, and Optimal Transport.

[BibT_eX]

[DOI]

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Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Parametric Resonance for Enhancing the Rate of Metastable Transition.

[BibT_eX]

[DOI]

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SIAM J. Appl. Math., June, 2022

Accurate and efficient simulations of Hamiltonian mechanical systems with discontinuous potentials.

[BibT_eX]

[DOI]

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J. Comput. Phys., 2022

Data-driven discovery of non-Newtonian astronomy via learning non-Euclidean Hamiltonian.

[BibT_eX]

[DOI]

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Evangelos A. Theodorou

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CoRR, 2022

Alternating Mirror Descent for Constrained Min-Max Games.

[BibT_eX]

[DOI]

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Georgios Piliouras

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Hessian-Free High-Resolution Nesterov Acceleration For Sampling.

[BibT_eX]

[DOI]

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Proceedings of the International Conference on Machine Learning, 2022

Large Learning Rate Tames Homogeneity: Convergence and Balancing Effect.

[BibT_eX]

[DOI]

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Proceedings of the Tenth International Conference on Learning Representations, 2022

Sqrt(d) Dimension Dependence of Langevin Monte Carlo.

[BibT_eX]

[DOI]

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Proceedings of the Tenth International Conference on Learning Representations, 2022

The Mirror Langevin Algorithm Converges with Vanishing Bias.

[BibT_eX]

[DOI]

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Santosh S. Vempala

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Proceedings of the International Conference on Algorithmic Learning Theory, 29 March, 2022

2021

A Derivative-Free Optimization Method With Application to Functions With Exploding and Vanishing Gradients.

[BibT_eX]

[DOI]

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IEEE Control. Syst. Lett., 2021

Data-driven Prediction of General Hamiltonian Dynamics via Learning Exactly-Symplectic Maps.

[BibT_eX]

[DOI]

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Proceedings of the 38th International Conference on Machine Learning, 2021

Variational Symplectic Accelerated Optimization on Lie Groups.

[BibT_eX]

[DOI]

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Proceedings of the 2021 60th IEEE Conference on Decision and Control (CDC), 2021

2020

AhKin: A modular and efficient code for the Doppler shift attenuation method.

[BibT_eX]

[DOI]

Alejandro Garzón

,

Wilmar Rodriguez

,

Fernando Cristancho

,

Comput. Phys. Commun., 2020

Improving Sampling Accuracy of Stochastic Gradient MCMC Methods via Non-uniform Subsampling of Gradients.

[BibT_eX]

[DOI]

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CoRR, 2020

Stochasticity of Deterministic Gradient Descent: Large Learning Rate for Multiscale Objective Function.

[BibT_eX]

[DOI]

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Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Why Do Deep Residual Networks Generalize Better than Deep Feedforward Networks? - A Neural Tangent Kernel Perspective.

[BibT_eX]

[DOI]

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Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Variational Optimization on Lie Groups, with Examples of Leading (Generalized) Eigenvalue Problems.

[BibT_eX]

[DOI]

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Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019

Data-driven multiscale decompositions for forecasting and model discovery.

[BibT_eX]

[DOI]

Daniel Dylewsky

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CoRR, 2019

Simply improved averaging for coupled oscillators and weakly nonlinear waves.

[BibT_eX]

[DOI]

Commun. Nonlinear Sci. Numer. Simul., 2019

Parametric Resonant Control of Macroscopic Behaviors of Multiple Oscillators.

[BibT_eX]

[DOI]

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Proceedings of the 2019 American Control Conference, 2019

2016

Explicit high-order symplectic integrators for charged particles in general electromagnetic fields.

[BibT_eX]

[DOI]

J. Comput. Phys., 2016

2015

Convex Optimal Uncertainty Quantification.

[BibT_eX]

[DOI]

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Richard M. Murray

SIAM J. Optim., 2015

2013

Variational integrators for electric circuits.

[BibT_eX]

[DOI]

Sina Ober-Blöbaum

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Jerrold E. Marsden

J. Comput. Phys., 2013

Convex optimal uncertainty quantification: Algorithms and a case study in energy storage placement for power grids.

[BibT_eX]

[DOI]

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Richard M. Murray

Proceedings of the American Control Conference, 2013

2010

Nonintrusive and Structure Preserving Multiscale Integration of Stiff ODEs, SDEs, and Hamiltonian Systems with Hidden Slow Dynamics via Flow Averaging.

[BibT_eX]

[DOI]

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Jerrold E. Marsden

Multiscale Model. Simul., 2010

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