Publications

Our publications provide insight into some of our leading-edge research.

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2025

Attention on the Sphere
Boris Bonev, Max Rietmann, Andrea Paris, Alberto Carpentieri, Thorsten Kurth
Augmenting Simulated Noisy Quantum Data Collection by Orders of Magnitude Using Pre-Trajectory Sampling with Batched Execution
Taylor Patti, Thien Nguyen, Justin Lietz, Alex McCaskey, Brucek Khailany
Isaac Lab: A GPU Accelerated Simulation Framework For Multi-Modal Robot Learning
Mayank Mittal, Kelly Guo, Gavriel State, Spencer Huang
Huge ensembles–Part 1: Design of ensemble weather forecasts using spherical Fourier neural operators
Ankur Mahesh, William D. Collins, Boris Bonev, Noah Brenowitz, Yair Cohen, Joshua Elms, Peter Harrington, Karthik Kashinath, Thorsten Kurth, Joshua North, Travis O'Brian, Mike Pritchard, David Pruitt, Mark Risser, Shashank Subramanian, Jared Willard
Huge ensembles – Part 2: Properties of a huge ensemble of hindcasts generated with spherical Fourier neural operators
Ankur Mahesh, William D. Collins, Boris Bonev, Noah Brenowitz, Yair Cohen, Peter Harrington, Karthik Kashinath, Thorsten Kurth, Joshua North, Travis O'Brian, Mike Pritchard, David Pruitt, Mark Risser, Shashank Subramanian, Jared Willard
FourCastNet 3: A geometric approach to probabilistic machine-learning weather forecasting at scale
Boris Bonev, Thorsten Kurth, Ankur Mahesh, Mauro Bisson, Jean Kossaifi, Karthik Kashinath, Anima Anandkumar, William D. Collins, Mike Pritchard, Alex Keller
Helix Parallelism: Rethinking Sharding Strategies for Interactive Multi-Million-Token LLM Decoding
Nidhi Bhatia, Ankit More, Ritika Borkar, Tiyasa Mitra, Ramon Matas, Ritchie Zhao, Maximilian Golub, Dheevatsa Mudigere, Brian Pharris, Bita Darvish Rouhani
Adaptive Algebraic Reuse of Reordering in Cholesky Factorizations with Dynamic Sparsity Patterns
Behrooz Zarebavani, Danny Kaufman, David Levin, Maryam Mehri Dehnavi
Sionna RT: Technical Report
Fayçal Aït Aoudia , Jakob Hoydis, Merlin Nimier-David, Sebastian Cammerer, Alex Keller
scene_synthesizer: A Python Library for Procedural Scene Generation in Robot Manipulation
Clemens Eppner, Adithya Murali, Caelan Garrett, Rowland O'Flaherty, Tucker Hermans, Wei Yang, Dieter Fox
Towards large-scale quantum optimization solvers with few qubits
Marco Sciorilli, Lucas Borges, Taylor Patti, Diego Garcia-Martin, Giancarlo Camilo, Anima Anandkumar, Leandro Aolita

2024

Pretraining codomain attention neural operators for solving multiphysics pdes
Md Ashiqur Rahman, Robert Joseph George, Mogab Elleithy, Daniel Leibovici, Zongyi Li, Boris Bonev, Colin White, Julius Berner, Raymond A. Yeh, Jean Kossaifi, Kamyar Azizzadenesheli, Anima Anandkumar
Differentiable GPU-Parallelized Task and Motion Planning
William Shen, Caelan Garrett, Nishanth Kumar, Ankit Goyal, Tucker Hermans, Leslie Pack Kaelbling, Tomás Lozano-Pérez, Fabio Ramos
Constructability-driven design of frame structures with state-space search methods
Yijiang Huang, Caelan Garrett, Caitlin Mueller
Conformer without Convolutions
Matthijs Van keirsbilck, Alex Keller
Zero and Finite Temperature Quantum Simulations Powered by Quantum Magic
Andi Gu, Hong-Ye Hu, Di Luo, Taylor Patti, Nicholas C. Rubin, Susanne F. Yelin
Neural operators with localized integral and differential kernels
Miguel Liu-Schiaffini, Julius Berner, Boris Bonev, Thorsten Kurth, Kamyar Azizzadenesheli, Anima Anandkumar
Improving Hyperparameter Optimization with Checkpointed Model Weights
Nikhil Mehta, Jonathan Lorraine, Steve Masson, Ramanathan Arunachalam, Zaid Pervaiz Bhat, James Lucas, Arun George Zachariah
Near-term distributed quantum computation using mean-field corrections and auxiliary qubits
Abigail McClain-Gomez, Taylor Patti, Anima Anandkumar, Susanne F. Yelin

2023

Compact Neural Graphics Primitives with Learned Hash Probing
Towaki Takikawa, Thomas Müller, Merlin Nimier-David, Alex Evans, Sanja Fidler, Alec Jacobson, Alex Keller
Graph Metanetworks for Processing Diverse Neural Architectures
Derek Lim, Haggai Maron, Marc T. Law, Jonathan Lorraine, James Lucas
Graph Neural Networks for Enhanced Decoding of Quantum LDPC Codes
Anqi Gong, Sebastian Cammerer, Joseph M. Renes
Spherical Fourier Neural Operators: Learning Stable Dynamics on the Sphere
Boris Bonev, Thorsten Kurth, Christian Hundt, Jaideep Pathak, Maximilian Baust, Karthik Kashinath, Anima Anandkumar

2022

Deep Learning-Based Synchronization for Uplink NB-IoT
Fayçal Aït Aoudia , Jakob Hoydis, Sebastian Cammerer, Matthijs Van keirsbilck, Alex Keller
Graph Neural Networks for Channel Decoding
Sebastian Cammerer, Jakob Hoydis, Fayçal Aït Aoudia , Alex Keller
Structural Pruning via Latency-Saliency Knapsack
Maying Shen, Hongxu Danny Yin, Pavlo Molchanov, Lei Mao, Jianna Liu, Jose M. Alvarez
From RTL to CUDA: A GPU Acceleration Flow for RTL Simulation with Batch Stimulus
Dian-Lun Lin, Mark Haoxing Ren, Yanqing Zhang, Brucek Khailany, Tsung-Wei Huang
As-Locally-Uniform-as-Possible Reshaping of Vector Clip Art
Chrystiano Araujo, Nicholas Vining, Enrique Rosales, Giorgio Gori, Alla Sheffer
Variable Bitrate Neural Fields
Towaki Takikawa, Alex Evans, Jonathan Tremblay, Thomas Müller, Morgan McGuire, Alec Jacobson, Sanja Fidler
Unbiased Inverse Volume Rendering With Differential Trackers
Merlin Nimier-David, Thomas Müller, Alex Keller, Wenzel Jakob
Generalized Resampled Importance Sampling: Foundations of ReSTIR
Daqi Lin, Markus Kettunen, Benedikt Bitterli, Jacopo Pantaleoni, Cem Yuksel, Chris Wyman
Unbiased and consistent rendering using biased estimators
Zackary Misso, Benedikt Bitterli, Iliyan Georgiev, Wojciech Jarosz