Fast and Green Computing with Graphics Processing Units for Solving Sparse Linear Systems. - Abal-Kassim Cheik Ahamed; Alban Desmaison; Frédéric Magoulès (HPCC/CSS/ICESS, 2014)

Power Consumption Analysis of Parallel Algorithms on GPUs. - Frédéric Magoulès; Abal-Kassim Cheik Ahamed; Alban Desmaison; Jean-Christophe Léchenet; François Mayer; Haifa Ben Salem; Thomas Zhu (HPCC/CSS/ICESS, 2014)

Efficient Continuous Relaxations for Dense CRF. - Alban Desmaison; Rudy Bunel; Pushmeet Kohli; Philip H. S. Torr; M. Pawan Kumar (ECCV (2), 2016)

Adaptive Neural Compilation. - Rudy Bunel; Alban Desmaison; Pawan Kumar Mudigonda; Pushmeet Kohli; Philip H. S. Torr (NIPS, 2016)

Playing Doom with SLAM-Augmented Deep Reinforcement Learning. - Shehroze Bhatti; Alban Desmaison; Ondrej Miksik; Nantas Nardelli; N. Siddharth 001; Philip H. S. Torr (CoRR, 2016)

Learning to superoptimize programs - Workshop Version. - Rudy Bunel; Alban Desmaison; M. Pawan Kumar; Philip H. S. Torr; Pushmeet Kohli (CoRR, 2016)

Inducing Interpretable Representations with Variational Autoencoders. - N. Siddharth 001; Brooks Paige; Alban Desmaison; Jan-Willem van de Meent; Frank D. Wood; Noah D. Goodman; Pushmeet Kohli; Philip H. S. Torr (CoRR, 2016)

Efficient Linear Programming for Dense CRFs. - Thalaiyasingam Ajanthan; Alban Desmaison; Rudy Bunel; Mathieu Salzmann; Philip H. S. Torr; M. Pawan Kumar (CVPR, 2017)

Learning to superoptimize programs. - Rudy Bunel; Alban Desmaison; M. Pawan Kumar; Philip H. S. Torr; Pushmeet Kohli (ICLR (Poster), 2017)

Learning Disentangled Representations with Semi-Supervised Deep Generative Models. - Siddharth Narayanaswamy; Brooks Paige; Jan-Willem van de Meent; Alban Desmaison; Noah D. Goodman; Pushmeet Kohli; Frank D. Wood; Philip H. S. Torr (NIPS, 2017)

PyTorch: An Imperative Style, High-Performance Deep Learning Library. - Adam Paszke; Sam Gross; Francisco Massa; Adam Lerer; James Bradbury; Gregory Chanan; Trevor Killeen; Zeming Lin; Natalia Gimelshein; Luca Antiga; Alban Desmaison; Andreas Köpf; et al. (NeurIPS, 2019)

Efficient Relaxations for Dense CRFs with Sparse Higher-Order Potentials. - Thomas Joy; Alban Desmaison; Thalaiyasingam Ajanthan; Rudy Bunel; Mathieu Salzmann; Pushmeet Kohli; Philip H. S. Torr; M. Pawan Kumar (SIAM J. Imaging Sci., 2019)

Optimization for, and by, machine learning. - Alban Desmaison (2019)

Lagrangian Decomposition for Neural Network Verification. - Rudy Bunel; Alessandro De Palma; Alban Desmaison; Krishnamurthy Dvijotham; Pushmeet Kohli; Philip H. S. Torr; M. Pawan Kumar (UAI, 2020)

Improved Branch and Bound for Neural Network Verification via Lagrangian Decomposition. - Alessandro De Palma; Rudy Bunel; Alban Desmaison; Krishnamurthy Dvijotham; Pushmeet Kohli; Philip H. S. Torr; M. Pawan Kumar (CoRR, 2021)

PyTorch RPC: Distributed Deep Learning Built on Tensor-Optimized Remote Procedure Calls. - Shen Li; Pritam Damania; Luca Wehrstedt; Rohan Varma; Omkar Salpekar; Pavel Belevich; Howard Huang; Yanli Zhao; Lucas Hosseini; Wanchao Liang; Hongyi Jia; Shihao Xu; et al. (MLSys, 2023)

Brief Industry Paper: Evaluating Robustness of Deep Learning-Based Recommendation Systems Against Hardware Errors: A Case Study. - Xun Jiao; Fan Fred Lin; Matt Xiao; Alban Desmaison; Daniel Moore; Sriram Sankar (RTSS, 2023)

PyTorch FSDP: Experiences on Scaling Fully Sharded Data Parallel. - Yanli Zhao; Andrew Gu; Rohan Varma; Liang Luo; Chien-Chin Huang; Min Xu; Less Wright; Hamid Shojanazeri; Myle Ott; Sam Shleifer; Alban Desmaison; Can Balioglu; et al. (CoRR, 2023)

Evaluating and Enhancing Robustness of Deep Recommendation Systems Against Hardware Errors. - Dongning Ma; Xun Jiao; Fan Fred Lin; Mengshi Zhang; Alban Desmaison; Thomas Sellinger; Daniel Moore; Sriram Sankar (CoRR, 2023)

PyTorch FSDP: Experiences on Scaling Fully Sharded Data Parallel. - Yanli Zhao; Andrew Gu; Rohan Varma; Liang Luo; Chien-Chin Huang; Min Xu; Less Wright; Hamid Shojanazeri; Myle Ott; Sam Shleifer; Alban Desmaison; Can Balioglu; et al. (Proc. VLDB Endow., 2023)

PyTorch 2: Faster Machine Learning Through Dynamic Python Bytecode Transformation and Graph Compilation. - Jason Ansel; Edward Z. Yang; Horace He; Natalia Gimelshein; Animesh Jain; Michael Voznesensky; Bin Bao; Peter Bell 008; David Berard; Evgeni Burovski; Geeta Chauhan; Anjali Chourdia; et al. (ASPLOS (2), 2024)

Dr. DNA: Combating Silent Data Corruptions in Deep Learning using Distribution of Neuron Activations. - Dongning Ma; Fan Fred Lin; Alban Desmaison; Joel Coburn; Daniel Moore; Sriram Sankar; Xun Jiao (ASPLOS (3), 2024)