Most of our publications can be found on arXiv. Citations: google scholar, orcid

2026

59

Non-Equilibrium Entropy Production and Information Dissipation in a Non-Markovian Quantum Dot

Shen, Yuejun; Chen, Chutian; Ma, Haoran; Saunders, Ashley P.; Heide, Christian; Liu, Fang; Rotskoff, Grant M.; Shi, Jiaojian; Lindenberg, Aaron M.

Nature Physics, 1745-2481, 1--8 (2026)

[doi]
58

Minimally dissipative multibit logical operations

Klinger, Jérémie; Rotskoff, Grant M.

Physical Review E 113(1), 014109 (2026)

[doi]
57

Scaling Transferable Coarse-graining with Mean Force Matching

Abigail Park; Shriram Chennakesavalu; Grant M. Rotskoff

pre-print: arXiv:2602.14531

[arXiv]
56

Efficient, Few-shot Directed Evolution with Energy Rank Alignment

Ibarraran, Sebastian; Chennakesavalu, Shriram; Hu, Frank; Rotskoff, Grant M.

, 2692-8205, 2026.02.03.703561

[doi]

2025

55

A Unified Approach to Analysis and Design of Denoising Markov Models

Yinuo Ren; Grant M. Rotskoff; Lexing Ying

Accepted in Journal of Machine Learning Research (2025)

pre-print: arXiv:2504.01938

[arXiv]
54

Aligning Transformers with Continuous Feedback via Energy Rank Alignment

Chennakesavalu, Shriram; Hu, Frank; Ibarraran, Sebastian; Rotskoff, Grant M.

The Thirty-ninth Annual Conference on Neural Information Processing Systems

pre-print: arXiv:2405.12961

[arXiv]
53

Fast Solvers for Discrete Diffusion Models: Theory and Applications of High-Order Algorithms

Ren, Yinuo; Chen, Haoxuan; Zhu, Yuchen; Guo, Wei; Chen, Yongxin; Rotskoff, Grant M.; Tao, Molei; Ying, Lexing

The Thirty-ninth Annual Conference on Neural Information Processing Systems

52

Nanoparticle Superlattices Assembled via Rapid Solvent Destabilization of Macromolecular Ligands

Ye, Matthew; Pert, Emmit K.; Lee, Margaret S.; Li, Yun; Nishimura, Arisa; Li, Rebecca L.; Ngo, Steven H.; Huang, Wen Yu; Rotskoff, Grant M.; Macfarlane, Robert J.

ACS Nano, 1936-0851 (2025)

[doi]
51

Coacervation Drives Morphological Diversity of mRNA Encapsulating Nanoparticles

Pert, Emmit K.; Hurst, Paul J.; Waymouth, Robert M.; Rotskoff, Grant M.

The Journal of Chemical Physics 162(7), 0021-9606, 074902 (2025)

[doi]
50

Morphology and depletion force-based large-scale self-assembly of nanocubes on surface"

Yeonhee Lee; Nicholas Juntunen; Seungsang Cha; Yuna Kwak; Grant M. Rotskoff; Jwa-Min Nam

In revision at \emphNature" (2025)

49

Pushing the limits of one-dimensional NMR spectroscopy for automated structure elucidation using artificial intelligence

Frank Hu; Jonathan M. Tubb; Dimitris Argyropoulos; Sergey Golotvin; Mikhail Elyashberg; Grant M. Rotskoff; Matthew W. Kanan; Thomas E. Markland

pre-print: arXiv:2512.18531

[arXiv]
48

DriftLite: Lightweight Drift Control for Inference-Time Scaling of Diffusion Models

Yinuo Ren; Wenhao Gao; Lexing Ying; Grant M. Rotskoff; Jiequn Han

ICLR 2026 (2025)

pre-print: arXiv:2509.21655

[arXiv]
47

Computing Nonequilibrium Responses with Score-Shifted Stochastic Differential Equations

Klinger, Jeremie; Rotskoff, Grant M.

Physical Review Letters *Editors' Suggestion* 134(9), 097101 (2025)

[doi]
46

Discrete Generative Diffusion Models without Stochastic Differential Equations: A Tensor Network Approach

Causer, Luke; Rotskoff, Grant M.; Garrahan, Juan P.

Physical Review E 111(2), 025302 (2025)

[doi]
45

Universal Energy-Speed-Accuracy Trade-Offs in Driven Nonequilibrium Systems

Klinger, Jeremie; Rotskoff, Grant M.

Physical Review E 111(1), 014114 (2025)

[doi]

2024

44

Features are fate: a theory of transfer learning in high-dimensional regression

Tahir, Javan; Ganguli, Surya; Rotskoff, Grant M.

Forty-second International Conference on Machine Learning ICML (2024)

pre-print: arXiv:2410.08194

[doi] [arXiv]
43

Statistical Spatially Inhomogeneous Diffusion Inference

Yinuo Ren; Yiping Lu; Lexing Ying; Grant M. Rotskoff

Thirty-Eighth AAAI Conference on Artificial Intelligence, AAAI, 14820--14828

pre-print: arXiv:2312.05793

[doi] [arXiv]
42

Accurate and Efficient Structure Elucidation from Routine One-Dimensional NMR Spectra Using Multitask Machine Learning

Hu, Frank; Chen, Michael S.; Rotskoff, Grant M.; Kanan, Matthew W.; Markland, Thomas E.

ACS Central Science 10(11), 2374-7943, 2162--2170 (2024)

pre-print: arXiv:2408.08284

[doi] [arXiv]
41

Accelerating Diffusion Models with Parallel Sampling: Inference at Sub-Linear Time Complexity

Chen, Haoxuan; Ren, Yinuo; Ying, Lexing; Rotskoff, Grant M.

The Thirty-eighth Annual Conference on Neural Information Processing Systems, *Spotlight Paper* (2024)

pre-print: arXiv:2405.15986

[arXiv]
40

Committor Guided Estimates of Molecular Transition Rates

Mitchell, Andrew R.; Rotskoff, Grant M.

Journal of Chemical Theory and Computation, 1549-9618 (2024)

pre-print: arXiv:2408.05879

[doi] [arXiv]
39

Power Dissipation and Entropy Production Rate of High-Dimensional Optical Matter Systems

Chen, Shiqi; Valenton, Emmanuel; Rotskoff, Grant M.; Ferguson, Andrew L.; Rice, Stuart A.; Scherer, Norbert F.

Physical Review E 110(4), 044109 (2024)

[doi]
38

Nanocrystal Assemblies: Current Advances and Open Problems

Bassani, Carlos L.; van Anders, Greg; Banin, Uri; Baranov, Dmitry; Chen, Qian; Dijkstra, Marjolein; Dimitriyev, Michael S.; Efrati, Efi; Faraudo, Jordi; Gang, Oleg; Gaston, Nicola; Golestanian, Ramin; Guerrero-Garcia, G. Ivan; Gruenwald, Michael; Haji-Akbari, Amir; Ibañez, Maria; Karg, Matthias; Kraus, Tobias; Lee, Byeongdu; Van Lehn, Reid C.; Macfarlane, Robert J.; Mognetti, Bortolo M.; Nikoubashman, Arash; Osat, Saeed; Prezhdo, Oleg V.; Rotskoff, Grant M.; Saiz, Leonor; Shi, An-Chang; Skrabalak, Sara; Smalyukh, Ivan I.; Tagliazucchi, Mario; Talapin, Dmitri V.; Tkachenko, Alexei V.; Tretiak, Sergei; Vaknin, David; Widmer-Cooper, Asaph; Wong, Gerard C. L.; Ye, Xingchen; Zhou, Shan; Rabani, Eran; Engel, Michael; Travesset, Alex

ACS Nano, 1936-0851 (2024)

[doi]
37

Microscopic Origin of Tunable Assembly Forces in Chiral Active Environments

Batton, Clay H.; Rotskoff, Grant M.

Soft Matter 20(20), 4111--4126 (2024)

pre-print: arXiv:2310.17763

[doi] [arXiv]
36

Sampling Thermodynamic Ensembles of Molecular Systems with Generative Neural Networks: Will Integrating Physics-Based Models Close the Generalization Gap?

Rotskoff, Grant M.

Current Opinion in Solid State and Materials Science 30, 1359-0286, 101158 (2024)

[doi]
35

Data-Efficient Generation of Protein Conformational Ensembles with Backbone-to-Side-Chain Transformers

Chennakesavalu, Shriram; Rotskoff, Grant M.

The Journal of Physical Chemistry B, 1520-6106 (2024)

pre-print: arXiv:2311.11459

[doi] [arXiv]
34

How Discrete and Continuous Diffusion Meet: Comprehensive Analysis of Discrete Diffusion Models via a Stochastic Integral Framework

Ren, Yinuo; Chen, Haoxuan; Rotskoff, Grant M.; Ying, Lexing

International Conference on Learning Representations, 2025 (2024)

[doi]
33

Adaptive Nonequilibrium Design of Actin-Based Metamaterials: Fundamental and Practical Limits of Control

Chennakesavalu, Shriram; Manikandan, Sreekanth K.; Hu, Frank; Rotskoff, Grant M.

Proceedings of the National Academy of Sciences 121(8), e2310238121 (2024)

pre-print: arXiv:2306.10778 [cond-mat.stat-mech]

[doi] [arXiv]
32

Computing Equilibrium Free Energies through a Nonequilibrium Quench

Liu, Kangxin; Rotskoff, Grant M.; Vanden-Eijnden, Eric; Hocky, Glen M.

The Journal of Chemical Physics 160(3), 0021-9606, 034109 (2024)

pre-print: arXiv:2309.05122

[doi] [arXiv]

2023

31

Unified, Geometric Framework for Nonequilibrium Protocol Optimization

Chennakesavalu, Shriram; Rotskoff, Grant M.

Physical Review Letters 130(10), 107101 (2023)

pre-print: arXiv:2205.01205

[doi] [arXiv]
30

Remembering the Work of Phillip L. Geissler: A Coda to His Scientific Trajectory

Bowman, Gregory R.; Cox, Stephen J.; Dellago, Christoph; DuBay, Kateri H.; Eaves, Joel D.; Fletcher, Daniel A.; Frechette, Layne B.; Grunwald, Michael; Klymko, Katherine; Ku, JiYeon; Omar, Ahmad; Rabani, Eran; Reichman, David R.; Rogers, Julia R.; Rosnik, Andreana M.; Rotskoff, Grant M.; Schneider, Anna R.; Schwierz, Nadine; Sivak, David A.; Vaikuntanathan, Suriyanarayanan; Whitelam, Stephen; Widmer-Cooper, Asaph

Annual Review of Physical Chemistry 74(1) (2023)

pre-print: arXiv:2302.13806

[doi] [arXiv]
29

Ensuring Thermodynamic Consistency with Invertible Coarse-Graining

Chennakesavalu, Shriram; Toomer, David J.; Rotskoff, Grant M.

The Journal of Chemical Physics Editor's Choice 2023 158(12), 0021-9606, 124126 (2023)

pre-print: arXiv:2210.07882

[doi] [arXiv]

2022

28

Learning Nonequilibrium Control Forces to Characterize Dynamical Phase Transitions

Yan, Jiawei; Touchette, Hugo; Rotskoff, Grant M.

Physical Review E 105(2), 024115 (2022)

pre-print: arXiv:2107.03348

[doi] [arXiv]
27

Trainability and Accuracy of Artificial Neural Networks: An Interacting Particle System Approach

Rotskoff, Grant; Vanden-Eijnden, Eric

Communications on Pure and Applied Mathematics 75(9), 1097-0312, 1889--1935 (2022)

pre-print: arXiv:1805.00915

[doi] [arXiv]
26

Physics-informed graph neural networks enhance scalability of variational nonequilibrium optimal control

Yan, Jiawei; Rotskoff, Grant M.

The Journal of Chemical Physics 157(7), 0021-9606, 074101 (2022)

pre-print: arXiv:2204.05493

[doi] [arXiv]
25

Adaptive Monte Carlo Augmented with Normalizing Flows

Gabrie, Marylou; Rotskoff, Grant M.; Vanden-Eijnden, Eric

Proc. Natl. Acad. Sci. U.S.A. 119(10), 0027-8424, 1091-6490, e2109420119 (2022)

pre-print: arXiv:2105.12603

[doi] [arXiv]

2021

24

Probing the Theoretical and Computational Limits of Dissipative Design

Chennakesavalu, Shriram; Rotskoff, Grant M.

J. Chem. Phys. 155(19), 0021-9606, 194114 (2021)

pre-print: arXiv:2108.05452

[doi] [arXiv]
23

Active Importance Sampling for Variational Objectives Dominated by

Grant M. Rotskoff and

Mathematical and Scientific Machine Learning, 16-19 August 2021, Virtual 145, 757--780

pre-print: arXiv:2008.06334

[arXiv]
22

Cooperative Multi-Agent Reinforcement Learning for High-Dimensional Nonequilibrium Control

Chennakesavalu, Shriram; Rotskoff, Grant M

Fourth Workshop on Machine Learning and the Physical Sciences NeurIPS 2021, 7

pre-print: arXiv:2111.06875

[arXiv]
21

Efficient Bayesian Sampling Using Normalizing Flows to Assist Markov Chain Monte Carlo Methods

Marylou Gabrie; Grant M. Rotskoff; Eric Vanden-Eijnden

ICML Workshop on Invertible Neural Networks, Normalizing Flows, and Explicit Likelihood Models ICML 2021

pre-print: arXiv:2107.08001

[arXiv]

2020

20

A Dynamical Central Limit Theorem for Shallow Neural Networks

Chen, Zhengdao; Rotskoff, Grant M.; Bruna, Joan; Vanden-Eijnden, Eric

Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, NeurIPS 2020, December 6-12, 2020, Virtual

pre-print: arXiv:2008.09623

[arXiv]
19

A Mean-Field Analysis of Two-Player Zero-Sum Games

Domingo-Enrich, Carles; Jelassi, Samy; Mensch, Arthur; Rotskoff, Grant M.; Bruna, Joan

Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, NeurIPS 2020, December 6-12, 2020, Virtual

pre-print: arXiv:2002.06277

[arXiv]

2019

18

Dynamical Computation of the Density of States and Bayes Factors Using Nonequilibrium Importance Sampling

Rotskoff, Grant M.; Vanden-Eijnden, Eric

Phys. Rev. Lett. 122(15), 0031-9007, 1079-7114, 150602 (2019)

pre-print: arXiv:1809.11132

[doi] [arXiv]
17

Neuron Birth-Death Dynamics Accelerates Gradient Descent and Converges Asymptotically

Rotskoff, Grant M.; Jelassi, Samy; Bruna, Joan; Vanden-Eijnden, Eric

Proceedings of the 36th International Conference on Machine Learning, ICML 2019, 9-15 June 2019, Long Beach, California, USA 97, 5508--5517

pre-print: arXiv:1902.01843

[arXiv]

2018

16

Robust Nonequilibrium Pathways to Microcompartment Assembly

Rotskoff, Grant M; Geissler, Phillip L

Proc. Natl. Acad. Sci. U.S.A 112, 201802499 (2018)

pre-print: arXiv:1709.00321

[doi] [arXiv]
15

Unraveling Kinetically-Driven Mechanisms of Gold Nanocrystal Shape Transformations Using Graphene Liquid Cell Electron Microscopy

Hauwiller, Matthew R.; Frechette, Layne B.; Jones, Matthew R.; Ondry, Justin C.; Rotskoff, Grant M.; Geissler, Phillip; Alivisatos, A. Paul

Nano Lett. 18(9), 1530-6984, 1530-6992, 5731--5737 (2018)

[doi]
14

Parameters as Interacting Particles: Long Time Convergence and Asymptotic Error Scaling of Neural Networks

Rotskoff, Grant M.; Vanden-Eijnden, Eric

Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, NeurIPS 2018, December 3-8, 2018, Montreal, Canada, 7146--7155

2017

13

Geometric approach to optimal nonequilibrium control: Minimizing dissipation in nanomagnetic spin systems

Rotskoff, Grant M.; Crooks, Gavin E.; Vanden-Eijnden, Eric

95(1), 2470-0045, 2470-0053, 012148

pre-print: arXiv:1607.07425

[doi] [arXiv]
12

Mapping Current Fluctuations of Stochastic Pumps to Nonequilibrium Steady States.

Rotskoff, Grant M

Phys. Rev. E 95(3-1), 030101 (2017)

pre-print: arXiv:1610.07586

[doi] [arXiv]
11

Inferring Dissipation from Current Fluctuations

Gingrich, Todd R; Rotskoff, Grant M; Horowitz, Jordan M

J. Phys. A: Math. Theor. 50(18), 184004 (2017)

pre-print: arXiv:1609.07131

[doi] [arXiv]
10

On the Role of Nonspherical Cavities in Short Length-Scale Density Fluctuations in Water

Sosso, Gabriele Cesare; Caravati, Sebastiano; Rotskoff, Grant; Vaikuntanathan, Suriyanarayan; Hassanali, Ali

J. Phys. Chem. A 121(1), 1089-5639, 1520-5215, 370--380 (2017)

[doi]

2016

9

Single-Particle Mapping of Nonequilibrium Nanocrystal Transformations

Ye, Xingchen; Jones, Matthew R; Frechette, Layne B; Chen, Qian; Powers, Alexander S; Ercius, Peter; Dunn, Gabriel; Rotskoff, Grant M; Nguyen, Son C; Adiga, Vivekananda P; Zettl, Alex; Rabani, Eran; Geissler, Phillip L; Alivisatos, A Paul

Science 354(6314), 874--877 (2016)

[doi]
8

Near-Optimal Protocols in Complex Nonequilibrium Transformations.

Gingrich, Todd R; Rotskoff, Grant M; Crooks, Gavin E; Geissler, Phillip L

Proc. Natl. Acad. Sci. U.S.A. 113(37), 10263--10268 (2016)

pre-print: arXiv:1602.01459

[doi] [arXiv]
7

Necessity of Capillary Modes in a Minimal Model of Nanoscale Hydrophobic Solvation.

Vaikuntanathan, Suriyanarayanan; Rotskoff, Grant; Hudson, Alexander; Geissler, Phillip L

Proc. Natl. Acad. Sci. U.S.A. 113(16), 201513659--30 (2016)

pre-print: arXiv:1507.02991

[doi] [arXiv]

2015

6

Optimal Control in Nonequilibrium Systems: Dynamic Riemannian Geometry of the Ising Model

Rotskoff, Grant M; Crooks, Gavin E

Phys. Rev. E 92(6), 060102 (2015)

[doi]
5

Structural Asymmetry in a Conserved Signaling System That Regulates Division, Replication, and Virulence of an Intracellular Pathogen.

Willett, Jonathan W; Herrou, Julien; Briegel, Ariane; Rotskoff, Grant; Crosson, Sean

Proc. Natl. Acad. Sci. U.S.A. 112(28), E3709--18 (2015)

[doi]
4

Molecular Simulation Workflows as Parallel Algorithms: The Execution Engine of Copernicus, a Distributed High-Performance Computing Platform.

Pronk, Sander; Pouya, Iman; Lundborg, Magnus; Rotskoff, Grant; Wesen, Bjorn; Kasson, Peter M; Lindahl, Erik

J. Chem. Theory Comput. 11(6), 2600--2608 (2015)

[doi]

2014

3

Efficiency and Large Deviations in Time-Asymmetric Stochastic Heat Engines

Gingrich, Todd R; Rotskoff, Grant M; Vaikuntanathan, Suriyanarayanan; Geissler, Phillip L

New J. Phys. 16(10), 102003 (2014)

pre-print: arXiv:1409.1561

[doi] [arXiv]
2

Transition-Tempered Metadynamics: Robust, Convergent Metadynamics via On-the-Fly Transition Barrier Estimation.

Dama, James F; Rotskoff, Grant; Parrinello, Michele; Voth, Gregory A

J. Chem. Theory Comput. 10(9), 3626--3633 (2014)

[doi]

2012

1

Structural Basis of a Protein Partner Switch That Regulates the General Stress Response of $\alpha$-Proteobacteria.

Herrou, Julien; Rotskoff, Grant; Luo, Yun; Roux, Benoit; Crosson, Sean

Proc. Natl. Acad. Sci. U.S.A. 109(21), E1415--23 (2012)

[doi]