Vineeth N Balasubramanian


Talks (Recent, Selected)

  • Explaining Neural Networks: A Causal Perspective, MILA Tea Talks, Feb 2021

  • Deep Learning: An Introduction and Recent Trends, ISRO Inertial Systems Unit, Feb 2021

  • Explaining Neural Networks: A Causal Perspective, NVIDIA GTC 2020 (Fall), Oct 2020

  • Introduction to Deep Learning and its Applications, INS Valsura Webinar on AI for Data-Driven Navy, Indian Navy, Oct 2020

  • Towards Explainable and Robust AI Practice, CII-IITH Power Talks 2.0 and Tech Edu Forum, Oct 2020

  • Object Detection Methods in Computer Vision, VSSC, Indian Space Research Organization, Sep 2020

  • Explaining Neural Networks: A Causal Perspective, Invited Talk, SPCOM 2020 (Virtual Conference), Jul 2020

  • Towards Explainable AI, NPTEL Live Series (Online), Apr 2020
    (Video)

  • Learning from Limited Labeled Data, Microsoft AI and Research & Facebook AI Research, CA, USA, Feb 2020; Microsoft, Hyderabad, May 2020

  • Zero-shot Task Transfer, CODS-COMAD Invited Paper Talk, Jan 2020; CVPR AC Workshop, San Diego, Feb 2020

  • Explaining Neural Networks: A Causal Perspective, MSR-LinkedIn-IISc FATE-ML Workshop, Bangalore, Jan 2020; Microsoft Research India, Bangalore, Feb 2020

  • Solving Next Generation of ML Problems: Learning from Limited Labeled Data, KLA Neoterix Conference, Keynote Talk, Chennai, Sep 2019; IBM Research India Labs, Feb 2020

  • Neural Network Attributions: A Causal Perspective, IIT-Madras, Jun 2019; IIT-Kanpur, Jul 2019

  • Towards Explainable Deep Learning, IIIT-Delhi, Mar 2019; IIT-ACB, Bangalore, May 2019; IISc Brain, Computation and Learning Workshop, Jun 2019

  • Zero-shot Task Transfer, IITH-RIKEN AI Workshop, IIT-Hyderabad, Mar 2019

  • Towards Explainable Deep Learning, AIST AIRC International Workshop, Tokyo, Feb 2019

  • Towards Explainable Deep Learning, NVIDIA AI Workshop, Bangalore, Feb 2019

  • Explainability in Machine/Deep Learning, IBM India Research Labs, Bangalore, Dec 2018

  • Towards Solving Next-Gen ML Problems: Learning with Weak Supervision, Intel ICTAI Workshop, Bangalore, Nov 2018

  • Machine Learning for Agriculture, International Workshop on Machine Learning for Cyber-Agricultural Systems (MLCAS2018), Keynote Talk, Mumbai, Oct 2018

  • Towards Solving Next-Gen ML Problems: Learning with Weak Supervision, NVIDIA DevConnect, Hyderabad, Sep 2018

  • Adversarial Data Programming: Using GANs to Relax the Bottleneck of Curated Labeled Data, ACCV Area Chairs Workshop, Nanyang Technological University, Sep 2018

  • Going beyond what and asking why: Explainability in Machine/Deep Learning, Anthill Inside 2018, Bangalore, Jul 2018
    (Video)

  • Optimization Methods in Deep Learning, 3rd Indian Workshop on Machine Learning, IIT-BHU, Jul 2018

  • Deep Generative Models for Annotated Image/Video Creation, NEC Labs, Cupertino, CA, Mar 2018

  • Deep Generative Models for Video Creation, NVIDIA GTC 2018, San Jose, CA, Mar 2018

  • Explainability in Deep Learning: Grad-CAM, Google AI/ML Workshop, Bangalore, Mar 2018

  • Recent Advances in Deep Learning Theory and Applications, Adobe, Noida, Feb 2018

  • Deep Learning: A Review, Microsoft Research-ACM Academic Research Summit, Hyderabad, Jan 2018
    (Video)