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David Meger

  1. Deep Reinforcement Learning that Matters
    2017/09/19 by Peter Henderson, Henderson, Peter, Riashat Islam +10 · 4 voices · 86 citations
    Computer Science · #Evolutionary Algorithms and Applications #Reinforcement Learning in Robotics #cs.LG #stat.ML
  2. Addressing Function Approximation Error in Actor-Critic Methods
    2018/02/26 by Scott Fujimoto, Herke van Hoof, Fujimoto, Scott +3 · 295 citations
    Computer Science · #Reinforcement Learning in Robotics
  3. For SALE: State-Action Representation Learning for Deep Reinforcement Learning
    2023/06/04 by Scott Fujimoto, Fujimoto, Scott, Wei-Di Chang +9 · 9 citations
    Computer Science · Engineering · Neuroscience · #Advanced Memory and Neural Computing #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Neural dynamics and brain function #Reinforcement Learning in Robotics
  4. 3D Shape Reconstruction from Vision and Touch
    2020/07/07 by Edward J. Smith, Smith, Edward J., Roberto Calandra +11 · 4 citations
    Computer Science · Engineering · #Advanced Vision and Imaging #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Hand Gesture Recognition Systems #Robot Manipulation and Learning #Robotics (cs.RO)
  5. Vision-Based Goal-Conditioned Policies for Underwater Navigation in the\n Presence of Obstacles
    2020/06/29 by Travis Manderson, Manderson, Travis, Juan Camilo Gamboa Higuera +11 · 3 citations
    Computer Science · Engineering · Environmental Science · #Coral and Marine Ecosystems Studies #FOS: Computer and information sciences #Multimodal Machine Learning Applications #Robotics (cs.RO) #Underwater Vehicles and Communication Systems
  6. Hypernetworks for Zero-shot Transfer in Reinforcement Learning
    2022/11/28 by Sahand Rezaei-Shoshtari, Rezaei-Shoshtari, Sahand, Charlotte Morissette +7 · 1 voice · 3 citations
    #cs.LG
  7. Normalizing Flow Ensembles for Rich Aleatoric and Epistemic Uncertainty Modeling
    2023/02/02 by Lucas Berry, Berry, Lucas, David Meger +1 · 2 citations
    Computer Science · Physics and Astronomy · #Machine Learning and Algorithms #Model Reduction and Neural Networks #Gaussian Processes and Bayesian Inference
  8. Parseval Regularization for Continual Reinforcement Learning
    2024/12/10 by Wesley Chung, Lynn Cherif, Chung, Wesley +5 · 4 citations
    Computer Science · #Machine Learning and ELM
  9. Distributional Hamilton-Jacobi-Bellman Equations for Continuous-Time Reinforcement Learning
    2022/05/24 by Harley Wiltzer, David Meger, Wiltzer, Harley +3 · 2 citations
    Computer Science · Decision Sciences · Physics and Astronomy · #Advanced Bandit Algorithms Research #Advanced Thermodynamics and Statistical Mechanics #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Optimization and Control (math.OC) #Reinforcement Learning in Robotics
  10. Generalizable Imitation Learning Through Pre-Trained Representations
    2023/11/15 by Wei-Di Chang, Chang, Wei-Di, Francois R. Hogan +6 · 2 citations
    Computer Science · #Artificial Intelligence (cs.AI) #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Human Pose and Action Recognition #Multimodal Machine Learning Applications #Robotics (cs.RO)
  11. Efficient Epistemic Uncertainty Estimation in Regression Ensemble Models Using Pairwise-Distance Estimators
    2023/08/25 by Lucas Berry, Berry, Lucas, David Meger +1 · 1 citation
    Computer Science · #Adversarial Robustness in Machine Learning #Gaussian Processes and Bayesian Inference #Anomaly Detection Techniques and Applications
  12. Action Gaps and Advantages in Continuous-Time Distributional Reinforcement Learning
    2024/10/14 by Harley Wiltzer, Marc G. Bellemare, Wiltzer, Harley +7 · 2 citations
    Computer Science · Engineering · #Adaptive Dynamic Programming Control #Extremum Seeking Control Systems #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Optimization and Control (math.OC) #Reinforcement Learning in Robotics