Poster reception - N-Body simulation on GPUs. - Erich Elsen; Mike Houston; Vaidyanathan Vishal; Eric Darve; Pat Hanrahan; Vijay S. Pande (SC, 2006)

N-Body Simulations on GPUs - Erich Elsen; Vaidyanathan Vishal; Mike Houston; Vijay S. Pande; Pat Hanrahan; Eric Darve (CoRR, 2007)

Large calculation of the flow over a hypersonic vehicle using a GPU. - Erich Elsen; Patrick LeGresley; Eric Darve (J. Comput. Phys., 2008)

Liszt: a domain specific language for building portable mesh-based PDE solvers. - Zach DeVito; Niels Joubert; Francisco Palacios; Stephen Oakley; Montserrat Medina; Mike Barrientos; Erich Elsen; Frank Ham; Alex Aiken; Karthik Duraisamy; Eric Darve; Juan J. Alonso; et al. (SC, 2011)

Deep Speech: Scaling up end-to-end speech recognition. - Awni Y. Hannun; Carl Case; Jared Casper; Bryan Catanzaro; Greg Diamos; Erich Elsen; Ryan Prenger; Sanjeev Satheesh; Shubho Sengupta; Adam Coates 002; Andrew Y. Ng (CoRR, 2014)

Deep Speech 2: End-to-End Speech Recognition in English and Mandarin. - Dario Amodei; Rishita Anubhai; Eric Battenberg; Carl Case; Jared Casper; Bryan Catanzaro; Jingdong Chen; Mike Chrzanowski; Adam Coates 002; Greg Diamos; Erich Elsen; Jesse H. Engel; et al. (CoRR, 2015)

Deep Speech 2 : End-to-End Speech Recognition in English and Mandarin. - Dario Amodei; Sundaram Ananthanarayanan; Rishita Anubhai; Jingliang Bai; Eric Battenberg; Carl Case; Jared Casper; Bryan Catanzaro; Jingdong Chen; Mike Chrzanowski; Adam Coates 002; Greg Diamos; et al. (ICML, 2016)

Persistent RNNs: Stashing Recurrent Weights On-Chip. - Greg Diamos; Shubho Sengupta; Bryan Catanzaro; Mike Chrzanowski; Adam Coates 002; Erich Elsen; Jesse H. Engel; Awni Y. Hannun; Sanjeev Satheesh (ICML, 2016)

DSD: Regularizing Deep Neural Networks with Dense-Sparse-Dense Training Flow. - Song Han 003; Jeff Pool; Sharan Narang; Huizi Mao; Shijian Tang; Erich Elsen; Bryan Catanzaro; John Tran; William J. Dally (CoRR, 2016)

DSD: Dense-Sparse-Dense Training for Deep Neural Networks. - Song Han 003; Jeff Pool; Sharan Narang; Huizi Mao; Enhao Gong; Shijian Tang; Erich Elsen; Peter Vajda; Manohar Paluri; John Tran; Bryan Catanzaro; William J. Dally (ICLR (Poster), 2017)

Exploring Sparsity in Recurrent Neural Networks. - Sharan Narang; Greg Diamos; Shubho Sengupta; Erich Elsen (ICLR (Poster), 2017)

Mixed Precision Training. - Paulius Micikevicius; Sharan Narang; Jonah Alben; Gregory F. Diamos; Erich Elsen; David García; Boris Ginsburg; Michael Houston; Oleksii Kuchaiev; Ganesh Venkatesh; Hao Wu (ICLR (Poster), 2018)

Efficient Neural Audio Synthesis. - Nal Kalchbrenner; Erich Elsen; Karen Simonyan; Seb Noury; Norman Casagrande; Edward Lockhart; Florian Stimberg; Aäron van den Oord; Sander Dieleman; Koray Kavukcuoglu (ICML, 2018)

Parallel WaveNet: Fast High-Fidelity Speech Synthesis. - Aäron van den Oord; Yazhe Li; Igor Babuschkin; Karen Simonyan; Oriol Vinyals; Koray Kavukcuoglu; George van den Driessche 002; Edward Lockhart; Luis C. Cobo; Florian Stimberg; Norman Casagrande; Dominik Grewe; et al. (ICML, 2018)

Onsets and Frames: Dual-Objective Piano Transcription. - Curtis Hawthorne; Erich Elsen; Jialin Song; Adam Roberts; Ian Simon; Colin Raffel; Jesse H. Engel; Sageev Oore; Douglas Eck (ISMIR, 2018)

Enabling Factorized Piano Music Modeling and Generation with the MAESTRO Dataset. - Curtis Hawthorne; Andriy Stasyuk; Adam Roberts; Ian Simon; Cheng-Zhi Anna Huang; Sander Dieleman; Erich Elsen; Jesse H. Engel; Douglas Eck (ICLR, 2019)

The State of Sparsity in Deep Neural Networks. - Trevor Gale; Erich Elsen; Sara Hooker (CoRR, 2019)

Non-Differentiable Supervised Learning with Evolution Strategies and Hybrid Methods. - Karel Lenc; Erich Elsen; Tom Schaul; Karen Simonyan (CoRR, 2019)

The Difficulty of Training Sparse Neural Networks. - Utku Evci; Fabian Pedregosa; Aidan N. Gomez; Erich Elsen (CoRR, 2019)

Fast Sparse ConvNets. - Erich Elsen; Marat Dukhan; Trevor Gale; Karen Simonyan (CVPR, 2020)

High Fidelity Speech Synthesis with Adversarial Networks. - Mikolaj Binkowski; Jeff Donahue; Sander Dieleman; Aidan Clark; Erich Elsen; Norman Casagrande; Luis C. Cobo; Karen Simonyan (ICLR, 2020)

Rigging the Lottery: Making All Tickets Winners. - Utku Evci; Trevor Gale; Jacob Menick; Pablo Samuel Castro; Erich Elsen (ICML, 2020)

On the Generalization Benefit of Noise in Stochastic Gradient Descent. - Samuel L. Smith; Erich Elsen; Soham De (ICML, 2020)

Top-KAST: Top-K Always Sparse Training. - Siddhant M. Jayakumar; Razvan Pascanu; Jack W. Rae; Simon Osindero; Erich Elsen (NeurIPS, 2020)

Sparse GPU kernels for deep learning. - Trevor Gale; Matei Zaharia; Cliff Young; Erich Elsen (SC, 2020)

A Practical Sparse Approximation for Real Time Recurrent Learning. - Jacob Menick; Erich Elsen; Utku Evci; Simon Osindero; Karen Simonyan; Alex Graves (CoRR, 2020)

AlgebraNets. - Jordan Hoffmann; Simon Schmitt; Simon Osindero; Karen Simonyan; Erich Elsen (CoRR, 2020)

End-to-end Adversarial Text-to-Speech. - Jeff Donahue; Sander Dieleman; Mikolaj Binkowski; Erich Elsen; Karen Simonyan (ICLR, 2021)

Practical Real Time Recurrent Learning with a Sparse Approximation. - Jacob Menick; Erich Elsen; Utku Evci; Simon Osindero; Karen Simonyan; Alex Graves (ICLR, 2021)

Scaling Language Models: Methods, Analysis & Insights from Training Gopher. - Jack W. Rae; Sebastian Borgeaud; Trevor Cai; Katie Millican; Jordan Hoffmann; H. Francis Song; John Aslanides; Sarah Henderson; Roman Ring; Susannah Young; Eliza Rutherford; Tom Hennigan; et al. (CoRR, 2021)

Step-unrolled Denoising Autoencoders for Text Generation. - Nikolay Savinov; Junyoung Chung; Mikolaj Binkowski; Erich Elsen; Aäron van den Oord (ICLR, 2022)

Improving Language Models by Retrieving from Trillions of Tokens. - Sebastian Borgeaud; Arthur Mensch; Jordan Hoffmann; Trevor Cai; Eliza Rutherford; Katie Millican; George van den Driessche 002; Jean-Baptiste Lespiau; Bogdan Damoc; Aidan Clark; Diego de Las Casas; Aurelia Guy; et al. (ICML, 2022)

Unified Scaling Laws for Routed Language Models. - Aidan Clark; Diego de Las Casas; Aurelia Guy; Arthur Mensch; Michela Paganini; Jordan Hoffmann; Bogdan Damoc; Blake A. Hechtman; Trevor Cai; Sebastian Borgeaud; George van den Driessche 002; Eliza Rutherford; et al. (ICML, 2022)

The State of Sparse Training in Deep Reinforcement Learning. - Laura Graesser; Utku Evci; Erich Elsen; Pablo Samuel Castro (ICML, 2022)

An empirical analysis of compute-optimal large language model training. - Jordan Hoffmann; Sebastian Borgeaud; Arthur Mensch; Elena Buchatskaya; Trevor Cai; Eliza Rutherford; Diego de Las Casas; Lisa Anne Hendricks; Johannes Welbl; Aidan Clark; Tom Hennigan; Eric Noland; et al. (NeurIPS, 2022)

Unified Scaling Laws for Routed Language Models. - Aidan Clark; Diego de Las Casas; Aurelia Guy; Arthur Mensch; Michela Paganini; Jordan Hoffmann; Bogdan Damoc; Blake A. Hechtman; Trevor Cai; Sebastian Borgeaud; George van den Driessche 002; Eliza Rutherford; et al. (CoRR, 2022)

Training Compute-Optimal Large Language Models. - Jordan Hoffmann; Sebastian Borgeaud; Arthur Mensch; Elena Buchatskaya; Trevor Cai; Eliza Rutherford; Diego de Las Casas; Lisa Anne Hendricks; Johannes Welbl; Aidan Clark; Tom Hennigan; Eric Noland; et al. (CoRR, 2022)