Papers I Read Notes and Summaries

Hierarchical RL Using an Ensemble of Proprioceptive Periodic Policies


  • The paper proposes a simple and robust approach for hierarchically training an agent in the sparse... Continue reading

Efficient Lifelong Learning with A-GEM


  • A new (and more realistic) evaluation protocol for lifelong learning where each data point is observed... Continue reading

Pre-training Graph Neural Networks with Kernels


  • The paper proposes a pretraining technique that can be used with the GNN architecture for... Continue reading

Smooth Loss Functions for Deep Top-k Classification


  • For top-k classification tasks, cross entropy is widely used as the learning objective even though it... Continue reading

Hindsight Experience Replay


  • Hindsight Experience Replay(HER) is a sample efficient technique to learn from sparse rewards.

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Representation Tradeoffs for Hyperbolic Embeddings


  • The paper describes a combinatorial approach to embed trees into hyperbolic spaces without performing optimization.

  • ... Continue reading

Learned Optimizers that Scale and Generalize


  • The paper introduces a learned gradient descent optimizer that has low memory and computational overhead and... Continue reading

One-shot Learning with Memory-Augmented Neural Networks


  • The paper demonstrates that Memory Augmented Neural Networks (MANN) are suitable for one-shot learning by introducing... Continue reading

BabyAI - First Steps Towards Grounded Language Learning With a Human In the Loop


  • BabyAI is a research platform to investigate and support the feasibility of including humans in the... Continue reading

Poincaré Embeddings for Learning Hierarchical Representations


  • Much of the work in representation leaning uses Euclidean vector spaces to embed datapoints (like words,... Continue reading