Aniket Didolkar

Aniket Didolkar

I am a Ph.D. Student at Mila, Montreal and The University of Montreal advised by Prof. Yoshua Bengio and Dr. Anirudh Goyal . Prior to joining my Ph.D., I was a masters student at Mila.

I received my bachelors degree in computer science from Manipal Institute of Technology, India . During my bachelors, I worked as a researcher at MIDAS Lab at IIIT Delhi advised by Professor Rajiv Ratn Shah . I have also interned at IISc Bangalore advised by Prof. Aditya Gopalan and Prof. Himanshu Tyagi for my bachelor's thesis on air quality monitoring and prediction.

I have also spent some time in the industry at Microsoft Research - NYC (Fall 2022), Ubisoft (Summer 2019) and Symbl.ai (summer 2018). I also spent the summer of 2019 building ChainerX -- an open source deep learning library -- as a part of Google Summer of Code.

CV / Email / Google Scholar / Twitter / Github

Recent News

Jan 2024: Paper titled Cycle Consistency Driven Object Discovery accepted at ICLR 2024.
June 2023: Started as a machine learning intern at Recursion Pharmaceuticals/Valence Labs advised by Dr. Jason Hartford.
May 2023: Started Ph.D. at Mila and The University of Montreal advised by Prof. Yoshua Bengio and Dr. Anirudh Goyal.
Sep 2022: Our work Temporal Latent Bottleneck: Synthesis of Fast and Slow Processing Mechanisms in Sequence Learning has been accepted to NeurIPS 2022!
Aug 2022: Joined Microsoft Research-NYC as a research intern!
April 2022: Awarded a scholarship worth $1500 by The University of Alberta and The Alberta Machine Intelligence Institute to visit Edmonton to attend the Amii AI week.
April 2022: Awarded a scholarship worth $4000 by The University of Montreal and The Quebec Ministry of Higher Education.
Jan 2022: Our work Coordination Among Neural Modules Through a Shared Global Workspace has been accepted for Oral presentation at ICLR 2022.
Oct 2021: Our work Systematic Evaluation of Causal Discovery in Visual Model-Based RL has been accepted at NeurIPS Dataset and Benchmark Track 2021.
Sep 2021: Our work Neural Production Systems has been accepted at NeurIPS 2021.
Aug 2021: Joined as a Research Master's Student at MILA
Feb 2021: Served in the program committee for ACL-IJCNLP 2021.
Oct 2020: Paper mixup for NLP accepted at COLING 2020.
Aug 2020: Joined as a Research Intern at MILA.
July 2020: Paper mixup for speech accepted at Interspeech 2020.
Jan 2020: Started as Research Intern at IISC Bangalore.
May 2019: Paper on arabic-hate speech profiling accepted at ACL-SRW 2019.
May 2019: Joined as an intern at Ubisoft India Studios.
May 2019: Accepted into Google Summer of Code 2019.
Apr 2019: Joined as a research intern at MIDAS Lab, IIIT Delhi.
Apr 2019: My paper for the ICLR Reproducibility Challenge 2019 was one of the 4 papers to be accepted to appear in the Journal of ReScience.

Research

I am interested in building models inspired by human inductive biases that can build on prior knowledge to solve various out-of-distribution scenarios.

	Cycle Consistency Driven Object Discovery Aniket Didolkar, Anirudh Goyal Yoshua Bengio ICLR 2024 arXiv Introduced auxillary objectives based on cycle consistency for unsupervised object discovery.
	Agent-Controller Representations : Principled Offline RL with Rich Exogenous Information Riashat Islam, Manan Tomar, Alex Lamb, Yonathan Efroni, Hongyu Zang, Aniket Didolkar, Dipendra Misra, Xin Li, Harm Van Seijen, Remi Tachet Des Combes, John Langford ICML 2023 arXiv Utilized the multi-step inverse dynamics objective for learning robust RL policies in noisy environments.
	Representation Learning in Deep RL with Discrete Information Bottleneck Riashat Islam, Hongyu Zang, Manan Tomar, Aniket Didolkar, Md Mofijul Islam, Anirudh Goyal, Samin Yeasar Arnob, Xin Li, Tariq Iqbal, Nicolas Hess, Alex Lamb. AISTATS 2023 arXiv Utilized discrete bottlenecks such as VQVAE to learn robust RL policies in noisy RL environments.
	Temporal Latent Bottleneck: Synthesis of Fast and Slow Processing Mechanisms in Sequence Learning Aniket Didolkar, Kshitij Gupta, Anirudh Goyal, Alex Lamb, Nan Rosemary Ke, Yoshua Bengio NeurIPS, 2022 arXiv / slides Introducing a recurrent stream into the Transformer architecture.
	Guaranteed Discovery of Controllable Latent States with Multi-Step Inverse Models Alex Lamb, Riashat Islam, Yonathan Efroni, Aniket Didolkar, Dipendra Misra, Dylan Foster, Lekan Molu, Rajan Chari, Akshay Krishnamurthy, John Langford, TMLR 2023 arXiv Algorithm for discovery of the minimal controllable latent state that has all the information for controlling an agent while learning to discard all other irrelevant information
	Coordination Among Neural Modules Through a Shared Global Workspace Anirudh Goyal, Aniket Didolkar, Alex Lamb, Kartikeya Badola, Nan Rosemary Ke, Nasim Rahaman, Jonathan Binas, Charles Blundell, Michael Mozer, Yoshua Bengio ICLR, 2022 (Oral Presentation - top 5% of accepted paper) arXiv Facilitating communication between modules using limited-capacity bottleneck.
	Neural Production Systems Aniket Didolkar, Anirudh Goyal, Nan Rosemary Ke, Charles Blundell, Philippe Beaudoin, Nicolas Heess, Michael Mozer, Yoshua Bengio NeurIPS, 2021 arXiv / open review Dynamically constructing sparse graphs for modulating communication between objects.
	Systematic Evaluation of Causal Discovery for Visual Model Based Reinforcement Learning Nan Rosemary Ke, Aniket Didolkar, Sarthak Mittal, Anirudh Goyal, Guillaume Lajoie, Stefan Bauer, Danilo Rezende, Yoshua Bengio, Michael Mozer, Christopher Pal NeurIPS Dataset and Benchmark Track, 2021 arXiv / NeurIPS Dataset and Benchmark Track Proceedings / Code A new and highly-flexible benchmark for evaluation of causal discovery in model-based RL.
	Augmenting NLP models using Latent Feature Interpolations Amit Jindal, Aniket Didolkar, Arijit Ghosh Chowdhury, Ramit Sawhney, Rajiv Ratn Shah, Di Jin Coling, 2020 PDF Proposed a new formulation of mixup for NLP.
	SpeechMix - Augmenting Deep Sound Recognition using Hidden Space Interpolations Amit Jindal, Narayanan Elavathur, Ranganatha, Aniket Didolkar, Arijit Ghosh Chowdhury, Ramit Sawhney, Rajiv Ratn Shah, Di Jin Interspeech, 2020 PDF Applied mixup in the domain of speech processing.
	ARHNet-Leveraging Community Interaction for Detection of Religious Hate Speech in Arabic Aniket Didolkar, Arijit Ghosh Chowdhury, Ramit Sawhney, Rajiv Shah ACL - Student Research Workshop, 2019 PDF Leveraging social media connectivity through a graph for profiling hate speech on twitter.
	[Re] h-detach: Modifying the LSTM gradient towards better optimization Aniket Didolkar ReScience, volume 5, issue 2 PDF Reproduced the paper h-detach: Modifying the LSTM gradient towards better optimization as a part of the ICLR 2019 reproducibility challenge.

Experience

	June 2023 - Present Machine Learning Intern Advisor - Dr. Jason Hartford
	Aug 2022 - Present Research Intern Advisor - Dr. Alex Lamb
	Aug 2021 - Present Graduate Student Researcher Advisors - Prof. Yoshua Bengio and Dr. Anirudh Goyal Aug 2020 - Aug 2021 Research Intern Advisors - Dr. Anirudh Goyal and Prof. Yoshua Bengio
	Jan 2020 - July 2020 Research Intern Advisors - Prof. Aditya Gopalan and Prof. Himanshu Tyagi
	April 2019 - Aug 2020 Research Intern Advisor - Prof. Rajiv Ratn Shah
	May 2019 - Aug 2019 Student Developer Organisation - NumFocus (Suborganisation - Chainer)
	May 2019 - July 2019 Automation Intern
	June 2018 - July 2018 Data Science Intern
	Feb 2018 - Feb 2019 Undergraduate Researcher