A streamlined Approach to Multimodal Few-Shot Class Incremental Learning for Fine-Grained Datasets.
CoRR, 2024
USE: Universal Segment Embeddings for Open-Vocabulary Image Segmentation.
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Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024
Hyp-OW: Exploiting Hierarchical Structure Learning with Hyperbolic Distance Enhances Open World Object Detection.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024
GradOrth: A Simple yet Efficient Out-of-Distribution Detection with Orthogonal Projection of Gradients.
CoRR, 2023
UP-DP: Unsupervised Prompt Learning for Data Pre-Selection with Vision-Language Models.
CoRR, 2023
Building a Subspace of Policies for Scalable Continual Learning.
Proceedings of the Eleventh International Conference on Learning Representations, 2023
Continual Learning Beyond a Single Model.
Proceedings of the Conference on Lifelong Learning Agents, 2023
Low-Rank Representation of Reinforcement Learning Policies.
J. Artif. Intell. Res., 2022
Efficient Continual Learning Ensembles in Neural Network Subspaces.
CoRR, 2022
Domain Adversarial Reinforcement Learning.
CoRR, 2021
Uncertainty quantification in skin cancer classification using three-way decision-based Bayesian deep learning.
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Comput. Biol. Medicine, 2021
Regularized Inverse Reinforcement Learning.
Proceedings of the 9th International Conference on Learning Representations, 2021
A Theoretical Analysis of Catastrophic Forgetting through the NTK Overlap Matrix.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021
Provably efficient reconstruction of policy networks.
CoRR, 2020
Deep Reinforcement and InfoMax Learning.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
Attraction-Repulsion Actor-Critic for Continuous Control Reinforcement Learning.
CoRR, 2019
Self-supervised Learning of Distance Functions for Goal-Conditioned Reinforcement Learning.
CoRR, 2019
Multi-objective training of Generative Adversarial Networks with multiple discriminators.
Proceedings of the 36th International Conference on Machine Learning, 2019
Leveraging exploration in off-policy algorithms via normalizing flows.
Proceedings of the 3rd Annual Conference on Robot Learning, 2019
On-Line Adaptative Curriculum Learning for GANs.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019
Online Adaptative Curriculum Learning for GANs.
CoRR, 2018
EmojiGAN: learning emojis distributions with a generative model.
Proceedings of the 9th Workshop on Computational Approaches to Subjectivity, 2018
Generating Realistic Sequences of Customer-Level Transactions for Retail Datasets.
Proceedings of the 2018 IEEE International Conference on Data Mining Workshops, 2018
Bayesian Policy Gradients via Alpha Divergence Dropout Inference.
CoRR, 2017