Research Areas

Research Areas

  • Efficient CDF Approximations for Normalizing Flows

    C.S. Sastry, A. Lehrmann, M. Brubaker, and A. Radovic. TMLR, 2022

    Learning And Generalization

    Publication

  • Agent Forecasting at Flexible Horizons using ODE Flows

    A. Radovic, J. He, J. Ramanan, M. Brubaker, and A. Lehrmann. ICML Workshop, 2021

    Time series Modelling

    Publication

  • PROVIDE: a probabilistic framework for unsupervised video decomposition

    P. Zablotskaia, E. A. Dominici, L. Sigal, and A. Lehrmann. UAI, 2021

    Computer Vision

    Publication

  • PUMA: Performance Unchanged Model Augmentation for Training Data Removal

    G. Wu, M. Hashemi, and C. Srinivasa. AAAI, 2022

    Learning And Generalization

    Publication

  • Why Exposure Bias Matters: An Imitation Learning Perspective of Error Accumulation in Language Generation

    K. Arora, L. El Asri, H. Bahuleyan, and J. Chi Kit Cheung. ACL, 2022

    Generative Models; Imitation Learning

    Publication

  • Generating Videos of Zero-Shot Compositions of Actions and Objects

    M. Nawhal, M. Zhai, A. Lehrmann, L. Sigal, and G. Mori. ECCV, 2020

    Computer Vision

    Publication

  • Stay Positive: Knowledge Graph Embedding Without Negative Sampling

    A. Hajimoradlou, and S. M. Kazemi. ICML Workshop, 2020

    Graph Representation Learning

    Publication

  • Continuous Latent Process Flows

    R. Deng, M. Brubaker, G. Mori, and A. Lehrmann. NeurIPS, 2021

    Time series Modelling

    Publication

  • SLAPS: Self-Supervision Improves Structure Learning for Graph Neural Networks

    B. Fatemi, L. El Asri, and S. M. Kazemi. NeurIPS, 2021

    Graph Representation Learning

    Publication

  • Not Too Close and Not Too Far Enforcing Monotonicity Requires Penalizing The Right Points

    J. Monteiro, M. O. Ahmed, H. Hajimirsadeghi, and G. Mori. NeurIPS Workshop, 2021

    Optimization; Responsible AI

    Publication

  • Robust Risk-Sensitive Reinforcement Learning Agents for Trading Markets

    *Y. Gao, K. Y. C. Lui, and P. Hernandez-Leal. ICML Workshop, 2021

    Reinforcement Learning

    Publication

  • Heterogeneous Multi-task Learning with Expert Diversity

    R. Aoki, F. Tung, and G. Oliveira. TCBB, 2022

    Learning And Generalization; Multi-task Learning

    Publication