Massa, Francisco

PyTorch: An Imperative Style, High-Performance Deep Learning Library

Paszke, A., Gross, S., Massa, F., Lerer, A., Bradbury, J., Chanan, G., Killeen, T., Lin, Z., Gimelshein, N., Antiga, L., et al. (2019) · arXiv

Parallel Computing and Optimization TechniquesComputational Physics and Python Applications

Cited by 31,473

End-to-End Object Detection with Transformers

Carion, N., Massa, F., Synnaeve, G., Usunier, N., Kirillov, A., & Zagoruyko, S. (2020) · Lecture Notes in Computer Science

Advanced Neural Network ApplicationsVisual Attention and Saliency Detection

Cited by 18,285

End-to-End Object Detection with Transformers

Carion, N., Massa, F., Synnaeve, G., Usunier, N., Kirillov, A., & Zagoruyko, S. (2020) · arXiv

Advanced Neural Network ApplicationsVisual Attention and Saliency Detection

Cited by 18,253

DINOv2: Learning Robust Visual Features without Supervision

Oquab, M., Darcet, T., Moutakanni, T., Vo, H., Szafraniec, M., Khalidov, V., Fernandez, P., Haziza, D., Massa, F., El-Nouby, A., et al. (2023) · arXiv

Domain Adaptation and Few-Shot LearningAdvanced Neural Network Applications

Cited by 1,078

Training data-efficient image transformers & distillation through attention

Touvron, H., Cord, M., Douze, M., Massa, F., Sablayrolles, A., & Jégou, H. (2020) · arXiv

Advanced Neural Network ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 182

V-JEPA 2: Self-Supervised Video Models Enable Understanding, Prediction and Planning

Assran, M., Bardes, A., Fan, D., Garrido, Q., Howes, R., Mojtaba, Komeili, Muckley, M., Rizvi, A., Roberts, C., et al. (2025) · arXiv

Human Pose and Action RecognitionMultimodal Machine Learning Applications

Cited by 8

CWM: An Open-Weights LLM for Research on Code Generation with World Models

FAIR CodeGen team, Copet, J., Carbonneaux, Q., Cohen, G., Gehring, J., Kahn, J., Kossen, J., Kreuk, F., McMilin, E., Meyer, M., et al. (2025) · arXiv

Software Engineering ResearchTopic Modeling

Cited by 0