Eugene Belilovsky

32 papers · 2016–2026 · 9 conferences · across top CS/AI conferences

Achievements

+12 more ↓

🐣 Hot Topic Early Bird 🌍 Conference Polyglot (9) 🧭 Keyword Pioneer 🌉 Interdisciplinary Bridge 🏃 Academic Marathon (10)

🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🌍 Conference Polyglot (9) 🤝 Dynamic Duo (10) 👑 Triple Crown 🏆 Grand Slam 🗃️ Keyword Collector (96) ❓ The Questioner ⚡ Prolific Year (5) 🚀 Conference Pioneer 💎 Century Club (32) 🔥 Unstoppable (11)

Conferences

ICML (8) ICLR (6) CVPR (4) NIPS (4) ECCV (3) WACV (3) ICCV (2) AAAI (1) JMLR (1)

Top co-authors

Edouard Oyallon (10) Michael Eickenberg (7) Guy Wolf (5) MohammadReza Davari (4) Muawiz Chaudhary (4) Rahaf Aljundi (4) Sudhir Mudur (3) Nader Asadi (3) Massimo Caccia (2) Tianhao Xie (2)

Keywords

catastrophic forgetting (3) convolutional neural network (3) continual learning (3) representation learning (3) domain adaptation (2) unsupervised learning (2) few-shot learning (2) neural network (2) contrastive learning (2) transfer learning (2) batch normalization (2) wavelet scattering transform (2) greedy learning (2) neural network training (2) knowledge distillation (1) preference learning (1) prototype learning (1) neural network optimization (1) neural network interpretation (1) distributed optimization (1)

Papers

End-to-End Fine-Tuning of 3D Texture Generation using Differentiable Rewards WACV 2026 Sketch-guided Cage-based 3D Gaussian Splatting Deformation WACV 2026 Test Time Adaptation Using Adaptive Quantile Recalibration WACV 2026 Accelerating Training with Neuron Interaction and Nowcasting Networks ICLR 2025 AdaFisher: Adaptive Second Order Optimization via Fisher Information ICLR 2025 PETRA: Parallel End-to-end Training with Reversible Architectures ICLR 2025 Adversarial Attacks on the Interpretation of Neuron Activation Maximization AAAI 2024 Harmony in Diversity: Merging Neural Networks with Canonical Correlation Analysis ICML 2024 Model Breadcrumbs: Scaling Multi-Task Model Merging with Sparse Masks ECCV 2024 Reliability of CKA as a Similarity Measure in Deep Learning ICLR 2023 $\textbf{A}^2\textbf{CiD}^2$: Accelerating Asynchronous Communication in Decentralized Deep Learning NIPS 2023 Guiding The Last Layer in Federated Learning with Pre-Trained Models NIPS 2023 Simulated Annealing in Early Layers Leads to Better Generalization CVPR 2023 Prototype-Sample Relation Distillation: Towards Replay-Free Continual Learning ICML 2023 Can Forward Gradient Match Backpropagation? ICML 2023 Towards Scaling Difference Target Propagation by Learning Backprop Targets ICML 2022 New Insights on Reducing Abrupt Representation Change in Online Continual Learning ICLR 2022 Parametric Scattering Networks CVPR 2022 Probing Representation Forgetting in Supervised and Unsupervised Continual Learning CVPR 2022 Revisiting Learnable Affines for Batch Norm in Few-Shot Transfer Learning CVPR 2022 The Unreasonable Effectiveness of Patches in Deep Convolutional Kernels Methods ICLR 2021 Generative Compositional Augmentations for Scene Graph Prediction ICCV 2021 Decoupled Greedy Learning of CNNs ICML 2020 Online Learned Continual Compression with Adaptive Quantization Modules ICML 2020 Few-Shot Single-View 3-D Object Reconstruction with Compositional Priors ECCV 2020 Kymatio: Scattering Transforms in Python JMLR 2020 Online Continual Learning with Maximal Interfered Retrieval NIPS 2019 Greedy Layerwise Learning Can Scale To ImageNet ICML 2019 Compressing the Input for CNNs with the First-Order Scattering Transform ECCV 2018 Scaling the Scattering Transform: Deep Hybrid Networks ICCV 2017 Learning to Discover Sparse Graphical Models ICML 2017 Testing for Differences in Gaussian Graphical Models: Applications to Brain Connectivity NIPS 2016