DL & DB Quick Notes

A collection of papers for DL and DB

Fields

• RL

  • Algorithms

    Here is Notes of papers

  • Curiosity

    Here is Notes of papers

  • Curricular Learning with RL

  • Distributed Training

  • Distributional RL

    Here is Notes of papers

  • Open-Ended RL

  • Real World Challenges

    Here is Notes of papers

  • Model-Based RL

    Here is Notes of papers

  • RL & Biology

  • Safe RL

    Here is Notes of papers

  • RL Applications

• Lottery Hypothesis & Pruning

  Here is the Notes of papers

  • Proving the Lottery Ticket Hypothesis Pruning is All You Need
  • The Lottery Ticket Hypothesis Finding Sparse Trainable Neural Networks
  • Rethinking The Value of Network Pruning
  • Dawing Early-Bird Tickets More Efficient Training of Deep Networks
  • Weight Agnostic Neural Networks
  • Learning Efficient Convolutional Networks through Network Slimming

• Neural Tangent Kerel(NTK)

  Notes

  • Wide Neural Networks of Any Depth Evolve as Linear Models Under Gradient Descent
  • DEEP INFORMATION PROPAGATION
  • The large learning rate phase of deep learning: the catapult mechanism

• Transformer

  Here is the Notes of papers

  • COMPRESSIVE TRANSFORMERS FOR LONG-RANGE SEQUENCE MODELLING
  • Transformer-XL: Attentive Language Models Beyond a Fixed-Length Context

• Meta-Learning

• BERT

• DL & Cyber Security

• DL Applications