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Nan Rosemary Ke

  1. A Deep Reinforcement Learning Chatbot
    2017/09/07 by Iulian V. Serban, Iulian Vlad Serban, Serban, Iulian V. +37 · 1 voice · 17 citations
    Computer Science · #Topic Modeling #Speech and dialogue systems #Mobile Crowdsensing and Crowdsourcing
  2. Toward Causal Representation Learning
    2021/02/26 by Bernhard Scholkopf, Bernhard Schölkopf, Francesco Locatello +5 · 178 citations
    Computer Science · #Bayesian Modeling and Causal Inference #Anomaly Detection Techniques and Applications #AI-based Problem Solving and Planning
  3. Towards Causal Representation Learning
    2021/02/22 by Bernhard Schölkopf, Schölkopf, Bernhard, Francesco Locatello +11 · 2 voices · 15 citations
    Computer Science · Decision Sciences · #Anomaly Detection Techniques and Applications #Artificial Intelligence (cs.AI) #Bayesian Modeling and Causal Inference #Data Quality and Management #FOS: Computer and information sciences #Machine Learning (cs.LG) #cs.AI #cs.LG
  4. Coordination Among Neural Modules Through a Shared Global Workspace
    2021/03/01 by Anirudh Goyal, Aniket Didolkar, Goyal, Anirudh +19 · 1 voice · 10 citations
    Computer Science · Engineering · Mathematics · #Ferroelectric and Negative Capacitance Devices #Reinforcement Learning in Robotics #Topic Modeling #cs.AI #cs.LG #stat.ML
  5. Learning Neural Causal Models from Unknown Interventions
    2019/10/02 by Nan Rosemary Ke, Olexa Bilaniuk, Ke, Nan Rosemary +10 · 13 citations
    Computer Science · #Artificial Intelligence (cs.AI) #Bayesian Modeling and Causal Inference #Explainable Artificial Intelligence (XAI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning in Healthcare
  6. Cascading Bandits for Large-Scale Recommendation Problems
    2016/03/17 by Shi Zong, Hao Ni, Zong, Shi +9 · 6 citations
    Computer Science · Decision Sciences · #Advanced Bandit Algorithms Research #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Optimization and Search Problems #Recommender Systems and Techniques
  7. AI-Assisted Generation of Difficult Math Questions
    2024/07/30 by Vedant Shah, Shah, Vedant, Dingli Yu +20 · 3 voices · 10 citations
    Computer Science · #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Intelligent Tutoring Systems and Adaptive Learning #Machine Learning (cs.LG) #Mathematics, Computing, and Information Processing #cs.AI #cs.LG
  8. A Deep Reinforcement Learning Chatbot (Short Version)
    2018/01/20 by Iulian V. Serban, Chinnadhurai Sankar, Serban, Iulian V. +33 · 1 voice
    #cs.CL #cs.AI #cs.LG #cs.NE #stat.ML
  9. On the Convergence of Continuous Constrained Optimization for Structure\n Learning
    2020/11/22 by Ignavier Ng, Sébastien Lachapelle, Ng, Ignavier +8 · 5 citations
    Computer Science · Engineering · #Advanced Graph Neural Networks #Bayesian Modeling and Causal Inference #Computational Drug Discovery Methods #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Molecular Junctions and Nanostructures #Neural Networks and Reservoir Computing
  10. Retrieval-Augmented Reinforcement Learning
    2022/02/17 by Goyal, Anirudh, Abram L. Friesen, Friesen, Abram L. +24 · 6 citations
    Computer Science · #Reinforcement Learning in Robotics #Data Stream Mining Techniques
  11. Learning Dynamics Model in Reinforcement Learning by Incorporating the Long Term Future
    2019/03/05 by Nan Rosemary Ke, Ke, Nan Rosemary, Amanpreet Singh +10 · 5 citations
    Computer Science · #Explainable Artificial Intelligence (XAI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Algorithms #Reinforcement Learning in Robotics
  12. Sparse Attentive Backtracking: Temporal CreditAssignment Through Reminding
    2018/09/11 by Nan Rosemary Ke, Anirudh Goyal, Ke, Nan Rosemary +11 · 2 citations
    Computer Science · #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Multimodal Machine Learning Applications #Reinforcement Learning in Robotics
  13. Learning Neural Causal Models with Active Interventions
    2021/09/06 by Nino Scherrer, Olexa Bilaniuk, Scherrer, Nino +17 · 2 citations
    Computer Science · #Bayesian Modeling and Causal Inference #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Algorithms
  14. Z-Forcing: Training Stochastic Recurrent Networks
    2017/11/15 by Anirudh Goyal, Goyal, Anirudh, Alessandro Sordoni +7 · 3 citations
    Computer Science · #FOS: Computer and information sciences #Generative Adversarial Networks and Image Synthesis #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Speech Recognition and Synthesis #Topic Modeling
  15. Can foundation models actively gather information in interactive environments to test hypotheses?
    2024/12/09 by Danny P. Sawyer, Sawyer, Danny P., Nan Rosemary Ke +25 · 3 voices · 2 citations
    Decision Sciences · Computer Science · #Scientific Computing and Data Management #Semantic Web and Ontologies #Data Visualization and Analytics
  16. Amortized learning of neural causal representations
    2020/08/21 by Nan Rosemary Ke, Jane X. Wang, Ke, Nan Rosemary +7 · 2 citations
    Computer Science · #Bayesian Modeling and Causal Inference #Domain Adaptation and Few-Shot Learning #Machine Learning in Healthcare
  17. Variational Walkback: Learning a Transition Operator as a Stochastic\n Recurrent Net
    2017/11/06 by Anirudh Goyal, Goyal, Anirudh, Nan Rosemary Ke +5 · 1 citation
    Computer Science · Physics and Astronomy · #Explainable Artificial Intelligence (XAI) #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Generative Adversarial Networks and Image Synthesis #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Model Reduction and Neural Networks #Neural Networks and Applications #Neural and Evolutionary Computing (cs.NE)
  18. Prequential MDL for Causal Structure Learning with Neural Networks
    2021/07/02 by Jörg Bornschein, Bornschein, Jorg, Silvia Chiappa +5 · 1 citation
    Computer Science · #Bayesian Modeling and Causal Inference #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Algorithms