Search Results for author: Ankesh Anand

Found 9 papers, 5 papers with code

Procedural Generalization by Planning with Self-Supervised World Models

no code implementations ICLR 2022 Ankesh Anand, Jacob Walker, Yazhe Li, Eszter Vértes, Julian Schrittwieser, Sherjil Ozair, Théophane Weber, Jessica B. Hamrick

One of the key promises of model-based reinforcement learning is the ability to generalize using an internal model of the world to make predictions in novel environments and tasks.

 Ranked #1 on Meta-Learning on ML10 (Meta-test success rate (zero-shot) metric)

Meta-Learning Model-based Reinforcement Learning +1

Data-Efficient Reinforcement Learning with Self-Predictive Representations

1 code implementation ICLR 2021 Max Schwarzer, Ankesh Anand, Rishab Goel, R. Devon Hjelm, Aaron Courville, Philip Bachman

We further improve performance by adding data augmentation to the future prediction loss, which forces the agent's representations to be consistent across multiple views of an observation.

Atari Games 100k Data Augmentation +4

Unsupervised State Representation Learning in Atari

3 code implementations NeurIPS 2019 Ankesh Anand, Evan Racah, Sherjil Ozair, Yoshua Bengio, Marc-Alexandre Côté, R. Devon Hjelm

State representation learning, or the ability to capture latent generative factors of an environment, is crucial for building intelligent agents that can perform a wide variety of tasks.

Atari Games Representation Learning

HoME: a Household Multimodal Environment

no code implementations29 Nov 2017 Simon Brodeur, Ethan Perez, Ankesh Anand, Florian Golemo, Luca Celotti, Florian Strub, Jean Rouat, Hugo Larochelle, Aaron Courville

We introduce HoME: a Household Multimodal Environment for artificial agents to learn from vision, audio, semantics, physics, and interaction with objects and other agents, all within a realistic context.

OpenAI Gym reinforcement-learning

We used Neural Networks to Detect Clickbaits: You won't believe what happened Next!

2 code implementations5 Dec 2016 Ankesh Anand, Tanmoy Chakraborty, Noseong Park

Online content publishers often use catchy headlines for their articles in order to attract users to their websites.

Clickbait Detection Feature Engineering

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