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The computational design of novel protein structures has the potential to impact numerous scientific disciplines greatly.
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Topics in Optimal Transportation
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Nanosecond to microsecond protein dynamics probed by magnetic relaxation dispersion of buried water molecules
Erik Persson and Bertil Halle · 2008
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Kemp elimination catalysts by computational enzyme design
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C. Villani · 2008
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Philip A Romero and Frances H Arnold · 2009
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Atomic-level characterization of the structural dynamics of proteins
David E. Shaw, Paul Maragakis, Kresten Lindorff-Larsen, Stefano Piana, Ron O. Dror, Michael P. Eastwood, Joseph A. Bank, John M. Jumper, John K. Salmon, Yibing Shan, and Willy Wriggers · 2010
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Computational design of proteins targeting the conserved stem region of influenza hemagglutinin
Sarel J Fleishman, Timothy A Whitehead, Damian C Ekiert, Cyrille Dreyfus, Jacob E Corn, Eva-Maria Strauch, Ian A Wilson, and David Baker · 2011
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Improved inverse scaling and squaring algorithms for the matrix logarithm
Awad H Al-Mohy and Nicholas J Higham · 2012
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Structure quality and target parameters
RA Engh and R Huber · 2012
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Lie groups, Lie algebras, and representations
Brian C Hall · 2013
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Isotropic Distributions for 3-dimension Rotations and One-sample Bayes Inference
Yu Qiu · 2013
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The coming of age of de novo protein design
Po-Ssu Huang, Scott E Boyken, and David Baker · 2016
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Wasserstein gan, 2017
Martin Arjovsky, Soumith Chintala, and Léon Bottou · 2017
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Density estimation using real nvp
Laurent Dinh, Jascha Sohl-Dickstein, and Samy Bengio · 2017
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Computational design of trimeric influenza-neutralizing proteins targeting the hemagglutinin receptor binding site
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DeepJDOT: Deep joint distribution optimal transport for unsupervised domain adaptation
Bharath Bhushan Damodaran, Benjamin Kellenberger, Remi Flamary, Devis Tuia, and Nicolas Courty · 2018
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Learning generative models with Sinkhorn divergences
Aude Genevay, Gabriel Peyre, and Marco Cuturi · 2018
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Improving gans using optimal transport, 2018
Tim Salimans, Han Zhang, Alec Radford, and Dimitris Metaxas · 2018
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Automating drug discovery
Gisbert Schneider · 2018
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Computational Optimal Transport
Gabriel Peyré and Marco Cuturi · 2019
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De novo design of potent and selective mimics of il-2 and il-15
Daniel-Adriano Silva, Shawn Yu, Umut Y Ulge, Jamie B Spangler, Kevin M Jude, Carlos Labão-Almeida, Lestat R Ali, Alfredo Quijano-Rubio, Mikel Ruterbusch, Isabel Leung, et al · 2019
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Machine-learning-guided directed evolution for protein engineering
Kevin K Yang, Zachary Wu, and Frances H Arnold · 2019
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Sampling using s u ( n ) su(n) gauge equivariant flows
Denis Boyda, Gurtej Kanwar, Sébastien Racanière, Danilo Jimenez Rezende, Michael S Albergo, Kyle Cranmer, Daniel C Hackett, and Phiala E Shanahan · 2020
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Learning with minibatch wasserstein : asymptotic and gradient properties
Kilian Fatras, Younes Zine, Rémi Flamary, Remi Gribonval, and Nicolas Courty · 2020
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How to train your neural ode: The world of jacobian and kinetic regularization
Chris Finlay, Jörn-Henrik Jacobsen, Levon Nurbekyan, and Adam M. Oberman · 2020
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Riemannian diffusion models
Chin-Wei Huang, Milad Aghajohari, Joey Bose, Prakash Panangaden, and Aaron C Courville · 2022
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Equivariant 3d-conditional diffusion models for molecular linker design
Ilia Igashov, Hannes Stärk, Clément Vignac, Victor Garcia Satorras, Pascal Frossard, Max Welling, Michael Bronstein, and Bruno Correia · 2022
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Bridge simulation and metric estimation on lie groups and homogeneous spaces
Mathias Højgaard Jensen, Lennard Hilgendorf, Sarang Joshi, and Stefan Sommer · 2022
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Denoising diffusion probabilistic models on so (3) for rotational alignment
Adam Leach, Sebastian M Schmon, Matteo T Degiacomi, and Chris G Willcocks · 2022
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Uni-fold: An open-source platform for developing protein folding models beyond alphafold
Ziyao Li, Xuyang Liu, Weijie Chen, Fan Shen, Hangrui Bi, Guolin Ke, and Linfeng Zhang · 2022
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Equivariant flow-based sampling for lattice gauge theory
Gurtej Kanwar, Michael S Albergo, Denis Boyda, Kyle Cranmer, Daniel C Hackett, Sébastien Racaniere, Danilo Jimenez Rezende, and Phiala E Shanahan · 2020
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Equivariant flows: exact likelihood generative learning for symmetric densities
Jonas Köhler, Leon Klein, and Frank Noé · 2020
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Riemannian continuous normalizing flows
Emile Mathieu and Maximilian Nickel · 2020
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Rethinking drug design in the artificial intelligence era
Petra Schneider, W Patrick Walters, Alleyn T Plowright, Norman Sieroka, Jennifer Listgarten, Robert A Goodnow Jr, Jasmin Fisher, Johanna M Jansen, José S Duca, Thomas S Rush, et al · 2020
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TrajectoryNet: A dynamic optimal transport network for modeling cellular dynamics
Alexander Tong, Jessie Huang, Guy Wolf, David van Dijk, and Smita Krishnaswamy · 2020
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Equivariant finite normalizing flows
Avishek Joey Bose and Ivan Kobyzev · 2021
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Manifold density estimation via generalized dequantization
James A. Brofos, Marcus A. Brubaker, and Roy R. Lederman · 2021
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Language models of protein sequences at the scale of evolution enable accurate structure prediction
Zeming Lin, Halil Akin, Roshan Rao, Brian Hie, Zhongkai Zhu, Wenting Lu, Nikita Smetanin, Allan dos Santos Costa, Maryam Fazel-Zarandi, Tom Sercu, Sal Candido, et al · 2022
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Flow matching for generative modeling, October 2022
Yaron Lipman, Ricky T. Q. Chen, Heli Ben-Hamu, Maximilian Nickel, and Matt Le · 2022
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Learning diffusion bridges on constrained domains
Xingchao Liu, Lemeng Wu, Mao Ye, et al · 2022
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Computational design of novel protein–protein interactions–an overview on methodological approaches and applications
Anthony Marchand, Alexandra K Van Hall-Beauvais, and Bruno E Correia · 2022
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Language models generalize beyond natural proteins
Robert Verkuil, Ori Kabeli, Yilun Du, Basile IM Wicky, Lukas F Milles, Justas Dauparas, David Baker, Sergey Ovchinnikov, Tom Sercu, and Alexander Rives · 2022
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Geodiff: A geometric diffusion model for molecular conformation generation
Minkai Xu, Lantao Yu, Yang Song, Chence Shi, Stefano Ermon, and Jian Tang · 2022
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Normalizing flows for lattice gauge theory in arbitrary space-time dimension (2023)
R Abbott, MS Albergo, A Botev, D Boyda, K Cranmer, DC Hackett, G Kanwar, AGDG Matthews, S Racaniere, A Razavi, et al · 2023
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Protein generation with evolutionary diffusion: sequence is all you need
Sarah Alamdari, Nitya Thakkar, Rianne van den Berg, Alex Xijie Lu, Nicolo Fusi, Ava Pardis Amini, and Kevin K Yang · 2023
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Building normalizing flows with stochastic interpolants
Michael S. Albergo and Eric Vanden-Eijnden · 2023
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Stochastic interpolants: A unifying framework for flows and diffusions
Michael S. Albergo, Nicholas M. Boffi, and Eric Vanden-Eijnden · 2023
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Edgi: Equivariant diffusion for planning with embodied agents
Johann Brehmer, Joey Bose, Pim De Haan, and Taco Cohen · 2023
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Riemannian flow matching on general geometries
Ricky TQ Chen and Yaron Lipman · 2023
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De novo design of protein interactions with learned surface fingerprints
Pablo Gainza, Sarah Wehrle, Alexandra Van Hall-Beauvais, Anthony Marchand, Andreas Scheck, Zander Harteveld, Stephen Buckley, Dongchun Ni, Shuguang Tan, Freyr Sverrisson, et al · 2023
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Unsupervised protein-ligand binding energy prediction via neural euler’s rotation equation
Wengong Jin, Siranush Sarkizova, Xun Chen, Nir Hacohen, and Caroline Uhler · 2023
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Leon Klein, Andreas Krämer, and Frank Noé · 2023
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Generating novel, designable, and diverse protein structures by equivariantly diffusing oriented residue clouds, 2023
Yeqing Lin and Mohammed AlQuraishi · 2023
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Large language models generate functional protein sequences across diverse families
Ali Madani, Ben Krause, Eric R Greene, Subu Subramanian, Benjamin P Mohr, James M Holton, Jose Luis Olmos Jr, Caiming Xiong, Zachary Z Sun, Richard Socher, et al · 2023
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Se (3) equivariant augmented coupling flows
Laurence I Midgley, Vincent Stimper, Javier Antorán, Emile Mathieu, Bernhard Schölkopf, and José Miguel Hernández-Lobato · 2023
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Diffusion Schrödinger bridge matching
Yuyang Shi, Valentin De Bortoli, Andrew Campbell, and Arnaud Doucet · 2023
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Aligned diffusion Schrödinger bridges
Vignesh Ram Somnath, Matteo Pariset, Ya-Ping Hsieh, Maria Rodriguez Martinez, Andreas Krause, and Charlotte Bunne · 2023
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Harmonic self-conditioned flow matching for multi-ligand docking and binding site design, 2023
Hannes Stärk, Bowen Jing, Regina Barzilay, and Tommi Jaakkola · 2023
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De novo design of protein structure and function with rfdiffusion
Joseph L. Watson, David Juergens, Nathaniel R. Bennett, Brian L. Trippe, Jason Yim, Helen E. Eisenach, Woody Ahern, Andrew J. Borst, Robert J. Ragotte, Lukas F. Milles, Basile I. M. Wicky, Nikita Hanikel, Samuel J. Pellock, Alexis Courbet, William Sheffler, Jue Wang, Preetham Venkatesh, Isaac Sappington, Susana Vázquez Torres, Anna Lauko, Valentin De Bortoli, Emile Mathieu, Sergey Ovchinnikov, Regina Barzilay, Tommi S. Jaakkola, Frank DiMaio, Minkyung Baek, and David Baker · 2023
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Towards predicting equilibrium distributions for molecular systems with deep learning
Shuxin Zheng, Jiyan He, Chang Liu, Yu Shi, Ziheng Lu, Weitao Feng, Fusong Ju, Jiaxi Wang, Jianwei Zhu, Yaosen Min, et al · 2023
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