Grant M. Rotskoff
Orcid: 0000-0002-7772-5179
According to our database1,
Grant M. Rotskoff
authored at least 16 papers
between 2018 and 2025.
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Bibliography
2025
Fast Solvers for Discrete Diffusion Models: Theory and Applications of High-Order Algorithms.
CoRR, February, 2025
2024
CoRR, 2024
How Discrete and Continuous Diffusion Meet: Comprehensive Analysis of Discrete Diffusion Models via a Stochastic Integral Framework.
CoRR, 2024
Accurate and efficient structure elucidation from routine one-dimensional NMR spectra using multitask machine learning.
CoRR, 2024
Discrete generative diffusion models without stochastic differential equations: a tensor network approach.
CoRR, 2024
Energy Rank Alignment: Using Preference Optimization to Search Chemical Space at Scale.
CoRR, 2024
Accelerating Diffusion Models with Parallel Sampling: Inference at Sub-Linear Time Complexity.
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024
2021
Efficient Bayesian Sampling Using Normalizing Flows to Assist Markov Chain Monte Carlo Methods.
CoRR, 2021
Active Importance Sampling for Variational Objectives Dominated by Rare Events: Consequences for Optimization and Generalization.
Proceedings of the Mathematical and Scientific Machine Learning, 2021
2020
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
2019
Neuron birth-death dynamics accelerates gradient descent and converges asymptotically.
Proceedings of the 36th International Conference on Machine Learning, 2019
2018
Neural Networks as Interacting Particle Systems: Asymptotic Convexity of the Loss Landscape and Universal Scaling of the Approximation Error.
CoRR, 2018
Parameters as interacting particles: long time convergence and asymptotic error scaling of neural networks.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018