الوحدات الحالية : | ALMASTY ALSOC APR BD CIAN ComplexNetworks DECISION DELYS LFI MOCAH MoVe NPA PEQUAN PolSys QI RO SMA SYEL |
الفـرق السـابـقــة : | ACASA |
- M. Cesaire, L. Schott, H. Hajri, S. Lamprier, P. Gallinari : “Stochastic Sparse Adversarial Attacks”, 2021 IEEE 33rd International Conference on Tools with Artificial Intelligence (ICTAI), Washington, United States, pp. 1247-1254, (IEEE) [Cesaire 2021]
- Ch. Corbière, M. Lafon, N. Thome, M. Cord, P. Pérez : “Beyond First-Order Uncertainty Estimation with Evidential Models for Open-World Recognition”, ICML 2021 Workshop on Uncertainty and Robustness in Deep Learning, Virtual, Austria [Corbière 2021a]
- C. Dancette, R. Cadene, D. Teney, M. Cord : “Beyond Question-Based Biases: Assessing Multimodal Shortcut Learning in Visual Question Answering”, 2021 International Conference on Computer Vision, Montreal, Canada [Dancette 2021a]
- C. Dancette, R. Cadene, X. Chen, M. Cord : “Learning Reasoning Mechanisms for Unbiased Question-based Counting”, VQA Workshop, CVPR 2021, Nashville, United States [Dancette 2021b]
- C. Dancette, R. Cadene, X. Chen, M. Cord : “Learning Reasoning Mechanisms for Unbiased Question-based Counting”, VQA Workshop,Conference on Computer Vision and Pattern Recognition 2021, Nashville, United States [Dancette 2021c]
- A. Dapogny, K. Bailly, M. Cord : “Deep Entwined Learning Head Pose and Face Alignment Inside an Attentional Cascade with Doubly-Conditional fusion”, 2020 15th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2020), Buenos Aires, Argentina, pp. 192-198, (IEEE) [Dapogny 2021]
- J. Donà, J.‑Y. Franceschi, S. Lamprier, P. Gallinari : “PDE-Driven Spatiotemporal Disentanglement”, The Ninth International Conference on Learning Representations, Vienne, Austria [Donà 2021a]
- J. Donà, P. Gallinari : “Differentiable Feature Selection, a Reparameterization Approach”, European Conference (ECML-PKDD), Virtual, France [Donà 2021c]
- A. Douillard, E. Valle, Ch. Ollion, Th. Robert, M. Cord : “Insights from the Future for Continual Learning”, CVPR Workshop, Nashville, United States, pp. 3477-3486, (IEEE) [Douillard 2021b]
- A. Douillard, T. Lesort : “Continuum: Simple Management of Complex Continual Learning Scenarios”, CVPR Workshop, Nashville, United States [Douillard 2021c]
- A. Douillard, Y. Chen, A. Dapogny, M. Cord : “PLOP: Learning without Forgetting for Continual Semantic Segmentation”, CVPR, Nashville, United States [Douillard 2021d]
- R. Dupont, H. Sahbi, G. Michel : “Weight Reparametrization for Budget-Aware Network Pruning”, 2021 IEEE International Conference on Image Processing (ICIP), Anchorage, AK (virtual), United States, pp. 789-793 [Dupont 2021]
- P. Erbacher, L. Soulier : “État de l'art des approches de modélisation et de simulation utilisateur pour la recherche d'information conversationnelle”, CORIA 2021, Grenoble, France [Erbacher 2021a]
- P. Erbacher, L. Soulier, L. Denoyer : “State of the Art of User Simulation approaches for conversational information retrieval”, CSR-Sim4IR 2021 Causality in Search and Recommendation and Simulation of Information Retrieval Evaluation 2021, Online, Canada [Erbacher 2021b]
- Th. Formal, B. Piwowarski, S. Clinchant : “A White Box Analysis of ColBERT”, 43rd EUROPEAN CONFERENCE ON INFORMATION RETRIEVAL, vol. 12657, Lecture Notes in Computer Science, Lucca (online), Italy, pp. 257-263, (Springer International Publishing) [Formal 2021a]
- Th. Formal, B. Piwowarski, S. Clinchant : “SPLADE: Sparse Lexical and Expansion Model for First Stage Ranking”, SIGIR '21: The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, Virtual Event, Canada, pp. 2288-2292, (ACM) [Formal 2021b]
- Th. Formal, B. Piwowarski, S. Clinchant : “Une Analyse du Modèle ColBERT”, Conférence en Recherche d’Information et Applications, Grenoble (virtuelle), France [Formal 2021c]
- V. Grari, O. Hajouji, S. Lamprier, M. Detyniecki : “Learning Unbiased Representations via Rényi Minimization”, European Conference on Machine Learning and Knowledge Discovery in Databases - ECML PKDD 2021, vol. 12976, Lecture Notes in Computer Science, Bilbao, Spain, pp. 749-764, (Springer International Publishing) [Grari 2021]
- N. Grinsztajn, Ph. Preux, E. Oyallon : “Low-Rank Projections of GCNs Laplacian”, ICLR 2021 Workshop GTRL, Online, France [Grinsztajn 2021b]
- M. Jiu, H. Sahbi : “DHCN: Deep Hierarchical Context Networks For Image Annotation”, ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Toronto, ON, Canada [Jiu 2021]
- V. Kashtanova, I. Ayed, N. Cedilnik, P. Gallinari, M. Sermesant : “EP-Net 2.0: Out-of-Domain Generalisation for Deep Learning Models of Cardiac Electrophysiology”, Functional Imaging and Modeling of the Heart, vol. 12738, Lecture Notes in Computer Science, Stanford, CA (virtual), United States, pp. 482-492, (Springer International Publishing) [Kashtanova 2021]
- O. Laousy, G. Chassagnon, E. Oyallon, N. Paragios, M.‑P. Revel, M. Vakalopoulou : “Deep Reinforcement Learning for L3 Slice Localization in Sarcopenia Assessment”, Machine Learning in Medical Imaging @MICCAI, vol. 12966, Lecture Notes in Computer Science, Strasbourg, France, pp. 317-326, (Springer) [Laousy 2021]
- J. Lovon, L. Soulier, K. Pinel‑Sauvagnat, L. Tamine : “Oubli Catastrophique et Modèles Neuronaux de Recherche d'Information”, 17ème conférence francophone en Recherche d’Information et Application (CORIA 2021), Grenoble (virtuel), France, pp. 1-5 [Lovon 2021a]
- J. Lovon, L. Soulier, K. Pinel‑Sauvagnat, L. Tamine : “Studying Catastrophic Forgetting in Neural Ranking Models”, ECIR 2021, vol. 12656, Lecture Notes in Computer Science (LNCS), Lucca (on line), Italy, pp. 375-390, (Springer International Publishing), (ISBN: 978-3-030-72112-1) [Lovon 2021b]
- Th. Luka, L. Soulier, D. Picard : “Apprentissage non supervisé de représentations de mots à l'aide de réseaux de convolution bilinéaires sur des caractères”, CORIA 2021, Grenoble (virtuel), France [Luka 2021a]
- Th. Luka, L. Soulier, D. Picard : “Unsupervised Word Representations Learning with Bilinear Convolutional Network on Characters”, The 29th European Symposium on Artificial Neural Networks, Online, Belgium, pp. 251-256 [Luka 2021b]
- A. Rame, M. Cord : “DICE: DIVERSITY IN DEEP ENSEMBLES VIA CONDITIONAL REDUNDANCY ADVERSARIAL ESTIMATION”, ICLR 2021 - 9th International Conference on Learning Representations, Vienne, Austria [Rame 2021a]
- A. Rame, R. Sun, M. Cord : “MixMo: Mixing Multiple Inputs for Multiple Outputs via Deep Subnetworks”, ICCV 2021, Paris, France, pp. 823-833 [Rame 2021b]
- C. Rebuffel, Th. Scialom, L. Soulier, B. Piwowarski, S. Lamprier, J. Staiano, G. Scoutheeten, P. Gallinari : “Data-QuestEval: A Reference-less Metric for Data-to-Text Semantic Evaluation”, 2021 Conference on Empirical Methods in Natural Language Processing (EMNLP), Punta Cana, Dominican Republic, pp. 8029-8036, (Association for Computational Linguistics) [Rebuffel 2021b]
- H. Sahbi : “Learning Laplacians in Chebyshev Graph Convolutional Networks”, 2021 IEEE/CVF International Conference on Computer Vision (ICCV), DLGC, Montreal (virtual), Canada, pp. 2064-2075 [Sahbi 2021a]
- H. Sahbi : “Lightweight Connectivity In Graph Convolutional Networks For Skeleton-Based Recognition”, 2021 IEEE International Conference on Image Processing (ICIP), Anchorage, AK (virtual), United States, pp. 2329-2333 [Sahbi 2021b]
- H. Sahbi, H. Zhan : “FFNB: Forgetting-Free Neural Blocks for Deep Continual Learning”, The British Machine Vision Conference (BMVC), Virtual, United Kingdom [Sahbi 2021c]
- H. Sahbi, S. Deschamps, A. Stoian : “Frugal Learning for Interactive Satellite Image Change Detection”, 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS, Brussels, Belgium, pp. 2811-2814 [Sahbi 2021d]
- A. Saporta, T.‑H. Vu, M. Cord, P. Pérez : “Multi-Target Adversarial Frameworks for Domain Adaptation in Semantic Segmentation”, IEEE/CVF International Conference on Computer Vision (ICCV), Montreal (virtuel), Canada [Saporta 2021]
- Th. Scialom, P.‑A. Dray, J. Staiano, S. Lamprier, B. Piwowarski : “To Beam Or Not To Beam: That is a Question of Cooperation for Language GANs”, Advances in Neural Information Processing Systems, vol. 34, Virtual, United States, pp. 26585-26597, (Curran Associates, Inc.) [Scialom 2021a]
- Th. Scialom, P.‑A. Dray, S. Lamprier, B. Piwowarski, J. Staiano, A. Wang, P. Gallinari : “QuestEval: Summarization Asks for Fact-based Evaluation”, 2021 Conference on Empirical Methods in Natural Language Processing, Online and Punta Cana, Dominican Republic, pp. 6594-6604, (Association for Computational Linguistics) [Scialom 2021b]
- B. Taillé, V. Guigue, G. Scoutheeten, P. Gallinari : “Separating Retention from Extraction in the Evaluation of End-to-end Relation Extraction”, Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, Punta Cana (online), Dominican Republic, pp. 10438–10449, (Association for Computational Linguistics) [Taillé 2021]
- L. Thiry, M. Arbel, E. Belilovsky, E. Oyallon : “The Unreasonable Effectiveness of Patches in Deep Convolutional Kernels Methods”, International Conference on Learning Representation (ICLR 2021), Vienna (online), Austria [Thiry 2021]
- T. Véniat, L. Denoyer, M. Ranzato : “Efficient Continual Learning with Modular Networks and Task-Driven Priors”, 9th International Conference on Learning Representations, ICLR 2021, Vienna, Austria [Véniat 2021]
- Y. Yin, V. Le Guen, J. Donà, I. Ayed, E. De Bézenac, N. Thome, P. Gallinari : “Augmenting physical models with deep networks for complex dynamics forecasting”, Ninth International Conference on Learning Representations ICLR 2021, Vienna (virtual), Austria [Yin 2021b]