Miguel Vasco - RankMe

45 papers A* 6A 7B 2Misc 2Journal 24Unranked 4

Year	Rank	Type	Title / Venue / Authors
2026	A*	`conf`	Centralized Training with Hybrid Execution in Multi-Agent Reinforcement Learning via Predictive Observation Imputation (Abstract Reprint). AAAI Pedro P. Santos, Diogo S. Carvalho, Miguel Vasco, Alberto Sardinha, Pedro A. Santos, Ana Paiva, Francisco S. Melo
2026	J	`jnl`	Geometry of Uncertainty: Learning Metric Spaces for Multimodal State Estimation in RL. CoRR Alfredo Reichlin, Adriano Pacciarelli, Danica Kragic, Miguel Vasco
2025	J	`jnl`	Centralized training with hybrid execution in multi-agent reinforcement learning via predictive observation imputation. Artif. Intell. Pedro P. Santos, Diogo S. Carvalho, Miguel Vasco, Alberto Sardinha, Pedro A. Santos, Ana Paiva, Francisco S. Melo
2025	Misc	`conf`	Deep Learning Amplified Early Stopping Bias: Overestimating Performance on Small Datasets. ICASSP Nona Rajabi, Antônio H. Ribeiro, Miguel Vasco, Danica Kragic
2025	A	`conf`	FLAME: A Federated Learning Benchmark for Robotic Manipulation. IROS Santiago Bou Betran, Alberta Longhini, Miguel Vasco, Yuchong Zhang, Danica Kragic
2025	J	`jnl`	FLAME: A Federated Learning Benchmark for Robotic Manipulation. CoRR Santiago Bou Betran, Alberta Longhini, Miguel Vasco, Yuchong Zhang, Danica Kragic
2025	J	`jnl`	FLoRA: Sample-Efficient Preference-based RL via Low-Rank Style Adaptation of Reward Functions. CoRR Daniel Marta, Simon Holk, Miguel Vasco, Jens Lundell, Timon Homberger, Finn Busch, Olov Andersson, Danica Kragic, Iolanda Leite
2025	A*	`conf`	Flora: Sample-Efficient Preference-Based Rl Via Low-Rank Style Adaptation of Reward Functions. ICRA Daniel Marta, Simon Holk, Miguel Vasco, Jens Lundell, Timon Homberger, Finn Busch, Olov Andersson, Danica Kragic, Iolanda Leite
2025	A*	`conf`	Human-Aligned Image Models Improve Visual Decoding from the Brain. ICML Nona Rajabi, Antônio H. Ribeiro, Miguel Vasco, Farzaneh Taleb, Mårten Björkman, Danica Kragic
2025	J	`jnl`	Human-Aligned Image Models Improve Visual Decoding from the Brain. CoRR Nona Rajabi, Antônio H. Ribeiro, Miguel Vasco, Farzaneh Taleb, Mårten Björkman, Danica Kragic
2025	J	`jnl`	Humans Co-exist, So Must Embodied Artificial Agents. CoRR Hannah Kuehn, Joseph La Delfa, Miguel Vasco, Danica Kragic, Iolanda Leite
2025	J	`jnl`	Walking on the Fiber: A Simple Geometric Approximation for Bayesian Neural Networks. CoRR Alfredo Reichlin, Miguel Vasco, Danica Kragic
2025	J	`jnl`	Walking on the Fiber: A Simple Geometric Approximation for Bayesian Neural Networks. Trans. Mach. Learn. Res. Alfredo Reichlin, Miguel Vasco, Danica Kragic
2024	J	`jnl`	A Super-human Vision-based Reinforcement Learning Agent for Autonomous Racing in Gran Turismo. RLJ Miguel Vasco, Takuma Seno, Kenta Kawamoto, Kaushik Subramanian, Peter R. Wurman, Peter Stone
2024	J	`jnl`	A Super-human Vision-based Reinforcement Learning Agent for Autonomous Racing in Gran Turismo. CoRR Miguel Vasco, Takuma Seno, Kenta Kawamoto, Kaushik Subramanian, Peter R. Wurman, Peter Stone
2024	A*	`conf`	Can Transformers Smell Like Humans? NeurIPS Farzaneh Taleb, Miguel Vasco, Antônio H. Ribeiro, Mårten Björkman, Danica Kragic
2024	J	`jnl`	Can Transformers Smell Like Humans? CoRR Farzaneh Taleb, Miguel Vasco, Antônio H. Ribeiro, Mårten Björkman, Danica Kragic
2024	A	`conf`	Centralized Training with Hybrid Execution in Multi-Agent Reinforcement Learning. AAMAS Pedro P. Santos, Diogo S. Carvalho, Miguel Vasco, Alberto Sardinha, Pedro A. Santos, Ana Paiva, Francisco S. Melo
2024	—	`conf`	Challenging Deep Learning Methods for EEG Signal Denoising under Data Corruption. EMBC Farzaneh Taleb, Miguel Vasco, Nona Rajabi, Mårten Björkman, Danica Kragic
2024	J	`jnl`	Goal-Conditioned Offline Reinforcement Learning via Metric Learning. CoRR Alfredo Reichlin, Miguel Vasco, Hang Yin, Danica Kragic
2024	A*	`conf`	NeuralSolver: Learning Algorithms For Consistent and Efficient Extrapolation Across General Tasks. NeurIPS Bernardo Esteves, Miguel Vasco, Francisco S. Melo
2024	J	`jnl`	NeuralThink: Algorithm Synthesis that Extrapolates in General Tasks. CoRR Bernardo Esteves, Miguel Vasco, Francisco S. Melo
2024	J	`jnl`	Reducing Variance in Meta-Learning via Laplace Approximation for Regression Tasks. CoRR Alfredo Reichlin, Gustaf Tegnér, Miguel Vasco, Hang Yin, Mårten Björkman, Danica Kragic
2024	J	`jnl`	Reducing Variance in Meta-Learning via Laplace Approximation for Regression Tasks. Trans. Mach. Learn. Res. Alfredo Reichlin, Gustaf Tegnér, Miguel Vasco, Hang Yin, Mårten Björkman, Danica Kragic
2024	—	`conf`	Will You Participate? Exploring the Potential of Robotics Competitions on Human-Centric Topics. HCI (2) Yuchong Zhang, Miguel Vasco, Mårten Björkman, Danica Kragic
2024	J	`jnl`	Will You Participate? Exploring the Potential of Robotics Competitions on Human-centric Topics. CoRR Yuchong Zhang, Miguel Vasco, Mårten Björkman, Danica Kragic
2023	B	`conf`	Detecting the Intention of Object Handover in Human-Robot Collaborations: An EEG Study. RO-MAN Nona Rajabi, Parag Khanna, Sümeyra Demir Kanik, Elmira Yadollahi, Miguel Vasco, Mårten Björkman, Christian Smith, Danica Kragic
2023	—	`conf`	Mental Face Image Retrieval Based on a Closed-Loop Brain-Computer Interface. HCI (9) Nona Rajabi, Charles Chernik, Alfredo Reichlin, Farzaneh Taleb, Miguel Vasco, Ali Ghadirzadeh, Mårten Björkman, Danica Kragic
2023	—	`conf`	Pre-training with Augmentations for Efficient Transfer in Model-Based Reinforcement Learning. EPIA (1) Bernardo Esteves, Miguel Vasco, Francisco S. Melo
2022	J	`jnl`	Centralized Training with Hybrid Execution in Multi-Agent Reinforcement Learning. CoRR Pedro P. Santos, Diogo S. Carvalho, Miguel Vasco, Alberto Sardinha, Pedro A. Santos, Ana Paiva, Francisco S. Melo
2022	J	`jnl`	GMC - Geometric Multimodal Contrastive Representation Learning. CoRR Petra Poklukar, Miguel Vasco, Hang Yin, Francisco S. Melo, Ana Paiva, Danica Kragic
2022	A*	`conf`	Geometric Multimodal Contrastive Representation Learning. ICML Petra Poklukar, Miguel Vasco, Hang Yin, Francisco S. Melo, Ana Paiva, Danica Kragic
2022	J	`jnl`	Leveraging hierarchy in multimodal generative models for effective cross-modality inference. Neural Networks Miguel Vasco, Hang Yin, Francisco S. Melo, Ana Paiva
2022	A	`conf`	Perceive, Represent, Generate: Translating Multimodal Information to Robotic Motion Trajectories. IROS Fábio Vital, Miguel Vasco, Alberto Sardinha, Francisco S. Melo
2022	J	`jnl`	Perceive, Represent, Generate: Translating Multimodal Information to Robotic Motion Trajectories. CoRR Fábio Vital, Miguel Vasco, Alberto Sardinha, Francisco S. Melo
2021	Misc	`conf`	Exploiting Symmetry in Human Robot-Assisted Dressing Using Reinforcement Learning. EPIA Pedro Ildefonso, Pedro Remédios, Rui Silva, Miguel Vasco, Francisco S. Melo, Ana Paiva, Manuela Veloso
2021	J	`jnl`	How to Sense the World: Leveraging Hierarchy in Multimodal Perception for Robust Reinforcement Learning Agents. CoRR Miguel Vasco, Hang Yin, Francisco S. Melo, Ana Paiva
2020	B	`conf`	Explainable Agency by Revealing Suboptimality in Child-Robot Learning Scenarios. ICSR Silvia Tulli, Marta Couto, Miguel Vasco, Elmira Yadollahi, Francisco S. Melo, Ana Paiva
2020	J	`jnl`	MHVAE: a Human-Inspired Deep Hierarchical Generative Model for Multimodal Representation Learning. CoRR Miguel Vasco, Francisco S. Melo, Ana Paiva
2020	A	`conf`	Multimodal Representation Learning for Robotic Cross-Modality Policy Transfer. AAMAS Miguel Vasco
2020	A	`conf`	Playing Games in the Dark: An Approach for Cross-Modality Transfer in Reinforcement Learning. AAMAS Rui Silva, Miguel Vasco, Francisco S. Melo, Ana Paiva, Manuela Veloso
2019	A	`conf`	Learning Multimodal Representations for Sample-efficient Recognition of Human Actions. IROS Miguel Vasco, Francisco S. Melo, David Martins de Matos, Ana Paiva, Tetsunari Inamura
2019	J	`jnl`	Learning multimodal representations for sample-efficient recognition of human actions. CoRR Miguel Vasco, Francisco S. Melo, David Martins de Matos, Ana Paiva, Tetsunari Inamura
2019	A	`conf`	Online Motion Concept Learning: A Novel Algorithm for Sample-Efficient Learning and Recognition of Human Actions. AAMAS Miguel Vasco, Francisco S. Melo, David Martins de Matos, Ana Paiva, Tetsunari Inamura
2019	J	`jnl`	Playing Games in the Dark: An approach for cross-modality transfer in reinforcement learning. CoRR Rui Silva, Miguel Vasco, Francisco S. Melo, Ana Paiva, Manuela Veloso