Generalized cyclic transformations in speaker-independent speech recognition. - Florian Müller 002; Eugene Belilovsky; Alfred Mertins (ASRU, 2009)

Predictive sparse modeling of fMRI data for improved classification, regression, and visualization using the k-support norm. - Eugene Belilovsky; Katerina Gkirtzou; Michail Misyrlis; Anna B. Konova; Jean Honorio; Nelly Alia-Klein; Rita Z. Goldstein; Dimitris Samaras; Matthew B. Blaschko (Comput. Medical Imaging Graph., 2015)

Convex relaxations of penalties for sparse correlated variables with bounded total variation. - Eugene Belilovsky; Andreas Argyriou; Gaël Varoquaux; Matthew B. Blaschko (Mach. Learn., 2015)

Testing for Differences in Gaussian Graphical Models: Applications to Brain Connectivity. - Eugene Belilovsky; Gaël Varoquaux; Matthew B. Blaschko (NIPS, 2016)

A Test of Relative Similarity For Model Selection in Generative Models. - Wacha Bounliphone; Eugene Belilovsky; Matthew B. Blaschko; Ioannis Antonoglou; Arthur Gretton (ICLR (Poster), 2016)

Fast Non-Parametric Tests of Relative Dependency and Similarity. - Wacha Bounliphone; Eugene Belilovsky; Arthur Tenenhaus; Ioannis Antonoglou; Arthur Gretton; Matthew B. Blaschko (CoRR, 2016)

Scaling the Scattering Transform: Deep Hybrid Networks. - Edouard Oyallon; Eugene Belilovsky; Sergey Zagoruyko (ICCV, 2017)

Joint Embeddings of Scene Graphs and Images. - Eugene Belilovsky; Matthew B. Blaschko; Jamie Ryan Kiros; Raquel Urtasun; Richard S. Zemel (ICLR (Workshop), 2017)

Learning to Discover Sparse Graphical Models. - Eugene Belilovsky; Kyle Kastner; Gaël Varoquaux; Matthew B. Blaschko (ICML, 2017)

Compressing the Input for CNNs with the First-Order Scattering Transform. - Edouard Oyallon; Eugene Belilovsky; Sergey Zagoruyko; Michal Valko (ECCV (9), 2018)

Blindfold Baselines for Embodied QA. - Ankesh Anand; Eugene Belilovsky; Kyle Kastner; Hugo Larochelle; Aaron C. Courville (CoRR, 2018)

Kymatio: Scattering Transforms in Python. - Mathieu Andreux; Tomás Angles; Georgios Exarchakis; Roberto Leonarduzzi; Gaspar Rochette; Louis Thiry; John Zarka; Stéphane Mallat; Joakim Andén; Eugene Belilovsky; Joan Bruna; Vincent Lostanlen; et al. (CoRR, 2018)

Structured Sparse Learning on Graphs in High-Dimensional Data with Applications to NeuroImaging. (Apprentissage de graphes structuré et parcimonieux dans des données de haute dimension avec applications à l'imagerie cérébrale). - Eugene Belilovsky (2018)

VideoNavQA: Bridging the Gap between Visual and Embodied Question Answering. - Catalina Cangea; Eugene Belilovsky; Aaron C. Courville (BMVC, 2019)

Greedy Layerwise Learning Can Scale To ImageNet. - Eugene Belilovsky; Michael Eickenberg; Edouard Oyallon (ICML, 2019)

Online Continual Learning with Maximal Interfered Retrieval. - Rahaf Aljundi; Eugene Belilovsky; Tinne Tuytelaars; Laurent Charlin; Massimo Caccia; Min Lin; Lucas Page-Caccia (NeurIPS, 2019)

VideoNavQA: Bridging the Gap between Visual and Embodied Question Answering. - Catalina Cangea; Eugene Belilovsky; Pietro Liò; Aaron C. Courville (ViGIL@NeurIPS, 2019)

Online Continual Learning with Maximally Interfered Retrieval. - Rahaf Aljundi; Lucas Caccia; Eugene Belilovsky; Massimo Caccia; Min Lin; Laurent Charlin; Tinne Tuytelaars (CoRR, 2019)

Online Learned Continual Compression with Stacked Quantization Module. - Lucas Caccia; Eugene Belilovsky; Massimo Caccia; Joelle Pineau (CoRR, 2019)

Scattering Networks for Hybrid Representation Learning. - Edouard Oyallon; Sergey Zagoruyko; Gabriel Huang; Nikos Komodakis; Simon Lacoste-Julien; Matthew B. Blaschko; Eugene Belilovsky (IEEE Trans. Pattern Anal. Mach. Intell., 2019)

Graph Density-Aware Losses for Novel Compositions in Scene Graph Generation. - Boris Knyazev 001; Harm de Vries; Catalina Cangea; Graham W. Taylor; Aaron C. Courville; Eugene Belilovsky (BMVC, 2020)

A Simple and Scalable Shape Representation for 3D Reconstruction. - Mateusz Michalkiewicz; Eugene Belilovsky; Mahsa Baktashmotlagh; Anders P. Eriksson (BMVC, 2020)

Few-Shot Single-View 3-D Object Reconstruction with Compositional Priors. - Mateusz Michalkiewicz; Sarah Parisot; Stavros Tsogkas; Mahsa Baktashmotlagh; Anders P. Eriksson; Eugene Belilovsky (ECCV (25), 2020)

Decoupled Greedy Learning of CNNs. - Eugene Belilovsky; Michael Eickenberg; Edouard Oyallon (ICML, 2020)

Online Learned Continual Compression with Adaptive Quantization Modules. - Lucas Caccia; Eugene Belilovsky; Massimo Caccia; Joelle Pineau (ICML, 2020)

Generative Graph Perturbations for Scene Graph Prediction. - Boris Knyazev 001; Harm de Vries; Catalina Cangea; Graham W. Taylor; Aaron C. Courville; Eugene Belilovsky (CoRR, 2020)

Kymatio: Scattering Transforms in Python. - Mathieu Andreux; Tomás Angles; Georgios Exarchakis; Roberto Leonarduzzi; Gaspar Rochette; Louis Thiry; John Zarka; Stéphane Mallat; Joakim Andén; Eugene Belilovsky; Joan Bruna; Vincent Lostanlen; et al. (J. Mach. Learn. Res., 2020)

Generative Compositional Augmentations for Scene Graph Prediction. - Boris Knyazev 001; Harm de Vries; Catalina Cangea; Graham W. Taylor; Aaron C. Courville; Eugene Belilovsky (ICCV, 2021)

The Unreasonable Effectiveness of Patches in Deep Convolutional Kernels Methods. - Louis Thiry; Michael Arbel; Eugene Belilovsky; Edouard Oyallon (ICLR, 2021)

Reducing Representation Drift in Online Continual Learning. - Lucas Caccia; Rahaf Aljundi; Tinne Tuytelaars; Joelle Pineau; Eugene Belilovsky (CoRR, 2021)

Decoupled Greedy Learning of CNNs for Synchronous and Asynchronous Distributed Learning. - Eugene Belilovsky; Louis Leconte; Lucas Caccia; Michael Eickenberg; Edouard Oyallon (CoRR, 2021)

Learning Compositional Shape Priors for Few-Shot 3D Reconstruction. - Mateusz Michalkiewicz; Stavros Tsogkas; Sarah Parisot; Mahsa Baktashmotlagh; Anders P. Eriksson; Eugene Belilovsky (CoRR, 2021)

Parametric Scattering Networks. - Shanel Gauthier; Benjamin Thérien; Laurent Alsène-Racicot; Irina Rish; Eugene Belilovsky; Michael Eickenberg; Guy Wolf (CoRR, 2021)

Probing Representation Forgetting in Supervised and Unsupervised Continual Learning. - MohammadReza Davari; Nader Asadi; Sudhir P. Mudur; Rahaf Aljundi; Eugene Belilovsky (CVPR, 2022)

Parametric Scattering Networks. - Shanel Gauthier; Benjamin Thérien; Laurent Alsène-Racicot; Muawiz Chaudhary; Irina Rish; Eugene Belilovsky; Michael Eickenberg; Guy Wolf (CVPR, 2022)

Revisiting Learnable Affines for Batch Norm in Few-Shot Transfer Learning. - Moslem Yazdanpanah; Aamer Abdul Rahman; Muawiz Chaudhary; Christian Desrosiers; Mohammad Havaei; Eugene Belilovsky; Samira Ebrahimi Kahou (CVPR, 2022)

New Insights on Reducing Abrupt Representation Change in Online Continual Learning. - Lucas Caccia; Rahaf Aljundi; Nader Asadi; Tinne Tuytelaars; Joelle Pineau; Eugene Belilovsky (ICLR, 2022)

Towards Scaling Difference Target Propagation by Learning Backprop Targets. - Maxence Ernoult; Fabrice Normandin; Abhinav Moudgil; Sean Spinney; Eugene Belilovsky; Irina Rish; Blake A. Richards; Yoshua Bengio (ICML, 2022)

CLIP-Mesh: Generating textured meshes from text using pretrained image-text models. - Nasir Mohammad Khalid; Tianhao Xie; Eugene Belilovsky; Tiberiu Popa (SIGGRAPH Asia, 2022)

Tackling Online One-Class Incremental Learning by Removing Negative Contrasts. - Nader Asadi; Sudhir P. Mudur; Eugene Belilovsky (CoRR, 2022)

Text to Mesh Without 3D Supervision Using Limit Subdivision. - Nasir Mohammad Khalid; Tianhao Xie; Eugene Belilovsky; Tiberiu Popa (CoRR, 2022)

Re-Weighted Softmax Cross-Entropy to Control Forgetting in Federated Learning. - Gwen Legate; Lucas Caccia; Eugene Belilovsky (CoLLAs, 2023)

Simulated Annealing in Early Layers Leads to Better Generalization. - AmirMohammad Sarfi; Zahra Karimpour; Muawiz Chaudhary; Nasir Mohammad Khalid; Mirco Ravanelli; Sudhir P. Mudur; Eugene Belilovsky (CVPR, 2023)

Reliability of CKA as a Similarity Measure in Deep Learning. - MohammadReza Davari; Stefan Horoi; Amine Natik; Guillaume Lajoie; Guy Wolf; Eugene Belilovsky (ICLR, 2023)

Prototype-Sample Relation Distillation: Towards Replay-Free Continual Learning. - Nader Asadi; MohammadReza Davari; Sudhir P. Mudur; Rahaf Aljundi; Eugene Belilovsky (ICML, 2023)

Can Forward Gradient Match Backpropagation? - Louis Fournier; Stéphane Rivaud; Eugene Belilovsky; Michael Eickenberg; Edouard Oyallon (ICML, 2023)

Guiding The Last Layer in Federated Learning with Pre-Trained Models. - Gwen Legate; Nicolas Bernier; Lucas Page-Caccia; Edouard Oyallon; Eugene Belilovsky (NeurIPS, 2023)

A2CiD2: Accelerating Asynchronous Communication in Decentralized Deep Learning. - Adel Nabli; Eugene Belilovsky; Edouard Oyallon (NeurIPS, 2023)

Local Learning with Neuron Groups. - Adeetya Patel; Michael Eickenberg; Eugene Belilovsky (CoRR, 2023)

Imitation from Observation With Bootstrapped Contrastive Learning. - Medric Sonwa; Johanna Hansen; Eugene Belilovsky (CoRR, 2023)

Continual Pre-Training of Large Language Models: How to (re)warm your model? - Kshitij Gupta; Benjamin Thérien; Adam Ibrahim; Mats L. Richter; Quentin Anthony; Eugene Belilovsky; Irina Rish; Timothée Lesort (CoRR, 2023)

DragD3D: Vertex-based Editing for Realistic Mesh Deformations using 2D Diffusion Priors. - Tianhao Xie; Eugene Belilovsky; Sudhir P. Mudur; Tiberiu Popa (CoRR, 2023)

Can We Learn Communication-Efficient Optimizers? - Charles-Étienne Joseph; Benjamin Thérien; Abhinav Moudgil; Boris Knyazev 001; Eugene Belilovsky (CoRR, 2023)

Gradient Masked Averaging for Federated Learning. - Irene Tenison; Sai Aravind Sreeramadas; Vaikkunth Mugunthan; Edouard Oyallon; Irina Rish; Eugene Belilovsky (Trans. Mach. Learn. Res., 2023)

Adversarial Attacks on the Interpretation of Neuron Activation Maximization. - Géraldin Nanfack; Alexander Fulleringer; Jonathan Marty; Michael Eickenberg; Eugene Belilovsky (AAAI, 2024)

Non-Uniform Parameter-Wise Model Merging. - Albert Manuel Orozco Camacho; Stefan Horoi; Guy Wolf; Eugene Belilovsky (IEEE Big Data, 2024)

Channel-Selective Normalization for Label-Shift Robust Test-Time Adaptation. - Pedro Vianna; Muawiz Sajjad Chaudhary; Paria Mehrbod; An Tang; Guy Cloutier; Guy Wolf; Michael Eickenberg; Eugene Belilovsky (CoLLAs, 2024)

Model Breadcrumbs: Scaling Multi-task Model Merging with Sparse Masks. - MohammadReza Davari; Eugene Belilovsky (ECCV (75), 2024)

Towards Motion from Video Diffusion Models. - Paul Janson; Tiberiu Popa; Eugene Belilovsky (ECCV Workshops (12), 2024)

Harmony in Diversity: Merging Neural Networks with Canonical Correlation Analysis. - Stefan Horoi; Albert Manuel Orozco Camacho; Eugene Belilovsky; Guy Wolf (ICML, 2024)

WASH: Train your Ensemble with Communication-Efficient Weight Shuffling, then Average. - Louis Fournier; Adel Nabli; Masih Aminbeidokhti; Marco Pedersoli; Eugene Belilovsky; Edouard Oyallon (CoRR, 2024)

μLO: Compute-Efficient Meta-Generalization of Learned Optimizers. - Benjamin Thérien; Charles-Étienne Joseph; Boris Knyazev 001; Edouard Oyallon; Irina Rish; Eugene Belilovsky (CoRR, 2024)

Temporally Consistent Object Editing in Videos using Extended Attention. - AmirHossein Zamani; Amir G. Aghdam; Tiberiu Popa; Eugene Belilovsky (CoRR, 2024)

From Feature Visualization to Visual Circuits: Effect of Adversarial Model Manipulation. - Géraldin Nanfack; Michael Eickenberg; Eugene Belilovsky (CoRR, 2024)

ACCO: Accumulate while you Communicate, Hiding Communications in Distributed LLM Training. - Adel Nabli; Louis Fournier; Pierre Erbacher; Louis Serrano; Eugene Belilovsky; Edouard Oyallon (CoRR, 2024)

Controlling Forgetting with Test-Time Data in Continual Learning. - Vaibhav Singh; Rahaf Aljundi; Eugene Belilovsky (CoRR, 2024)

Not Only the Last-Layer Features for Spurious Correlations: All Layer Deep Feature Reweighting. - Humza Wajid Hameed; Géraldin Nanfack; Eugene Belilovsky (CoRR, 2024)

Sketch-guided Cage-based 3D Gaussian Splatting Deformation. - Tianhao Xie; Noam Aigerman; Eugene Belilovsky; Tiberiu Popa (CoRR, 2024)

Simple and Scalable Strategies to Continually Pre-train Large Language Models. - Adam Ibrahim; Benjamin Thérien; Kshitij Gupta; Mats L. Richter; Quentin Gregory Anthony; Eugene Belilovsky; Timothée Lesort; Irina Rish (Trans. Mach. Learn. Res., 2024)

Accelerating Training with Neuron Interaction and Nowcasting Networks. - Boris Knyazev 001; Abhinav Moudgil; Guillaume Lajoie; Eugene Belilovsky; Simon Lacoste-Julien (ICLR, 2025)

AdaFisher: Adaptive Second Order Optimization via Fisher Information. - Damien Martins Gomes; Yanlei Zhang; Eugene Belilovsky; Guy Wolf; Mahdi S. Hosseini (ICLR, 2025)

PETRA: Parallel End-to-end Training with Reversible Architectures. - Stéphane Rivaud; Louis Fournier; Thomas Pumir; Eugene Belilovsky; Michael Eickenberg; Edouard Oyallon (ICLR, 2025)

Meta-learning Optimizers for Communication-Efficient Learning. - Charles-Étienne Joseph; Benjamin Thérien; Abhinav Moudgil; Boris Knyazev 001; Eugene Belilovsky (Trans. Mach. Learn. Res., 2025)

Celo: Training Versatile Learned Optimizers on a Compute Diet. - Abhinav Moudgil; Boris Knyazev 001; Guillaume Lajoie; Eugene Belilovsky (Trans. Mach. Learn. Res., 2025)

Learning Versatile Optimizers on a Compute Diet. - Abhinav Moudgil; Boris Knyazev 001; Guillaume Lajoie; Eugene Belilovsky (CoRR, 2025)

FairDropout: Using Example-Tied Dropout to Enhance Generalization of Minority Groups. - Géraldin Nanfack; Eugene Belilovsky (CoRR, 2025)

Beyond Cosine Decay: On the effectiveness of Infinite Learning Rate Schedule for Continual Pre-training. - Vaibhav Singh; Paul Janson; Paria Mehrbod; Adam Ibrahim; Irina Rish; Eugene Belilovsky; Benjamin Thérien (CoRR, 2025)

Continual Pre-training of MoEs: How robust is your router? - Benjamin Thérien; Charles-Étienne Joseph; Zain Sarwar; Ashwinee Panda; Anirban Das; Shi-Xiong Zhang 001; Stephen Rawls; Sambit Sahu; Eugene Belilovsky; Irina Rish (CoRR, 2025)

Incentivizing Permissionless Distributed Learning of LLMs. - Joel Lidin; Amir Sarfi; Evangelos Pappas; Samuel Dare; Eugene Belilovsky; Jacob Steeves (CoRR, 2025)

MuLoCo: Muon is a practical inner optimizer for DiLoCo. - Benjamin Thérien; Xiaolong Huang; Irina Rish; Eugene Belilovsky (CoRR, 2025)

PyLO: Towards Accessible Learned Optimizers in PyTorch. - Paul Janson; Benjamin Thérien; Quentin Anthony; Xiaolong Huang; Abhinav Moudgil; Eugene Belilovsky (CoRR, 2025)

Less is More: Undertraining Experts Improves Model Upcycling. - Stefan Horoi; Guy Wolf; Eugene Belilovsky; Gintare Karolina Dziugaite (CoRR, 2025)

Geometry-Aware Preference Learning for 3D Texture Generation. - AmirHossein Zamani; Tianhao Xie; Amir G. Aghdam; Tiberiu Popa; Eugene Belilovsky (CoRR, 2025)

Model Parallelism With Subnetwork Data Parallelism. - Vaibhav Singh; Zafir Khalid; Edouard Oyallon; Eugene Belilovsky (CoRR, 2025)

Rethinking Prompt Optimization: Reinforcement, Diversification, and Migration in Blackbox LLMs. - MohammadReza Davari; Utkarsh Garg; Weixin Cai; Eugene Belilovsky (CoRR, 2025)

Communication Efficient LLM Pre-training with SparseLoCo. - Amir Sarfi; Benjamin Thérien; Joel Lidin; Eugene Belilovsky (CoRR, 2025)