Gantavya Bhatt's repositories
Decay-RNN-ACL-SRW2020
This is an official pytorch implementation for the experiments described in the paper - "How much complexity does an RNN architecture need to learn syntax-sensitive dependencies?", Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics: Student Research Workshop
Papers-I-found-useful-till-the-current-time-
An attempt to maintain a record of papers I have read so far.
Binary-Symmetric-Channel-Coding
Model for Binary Symmetric Channel decoded with joint typicality decoder.
COVID_Literature
In this repo, I will try to keep the links to the important papers related to computational methods for Viruses.
UnsupervisedScalableRepresentationLearningTimeSeries
Unsupervised Scalable Representation Learning for Multivariate Time Series: Experiments
Transformer-scratch
implementation of transformer network from scratch
Asymptotic_Equipartition_Property
Visualization of AEP and other information theoretic aspects.
atari-representation-learning
Code for "Unsupervised State Representation Learning in Atari"
Cloud-Storage
The Repository contains the Deduplication algorithms used in the cloud storage.
computation-thru-dynamics
Understanding computation in artificial and biological recurrent networks through the lens of dynamical systems.
ffcv-imagenet
Train ImageNet *fast* in 500 lines of code with FFCV
GerryFair
library for fair auditing and learning of classifiers with respect to rich subgroup fairness.
google-research
Google AI Research
natural-adv-examples
A Harder ImageNet Test Set (CVPR 2021)
nlp-for-sanskrit
State of the Art Language models and Classifier for Sanskrit language (ancient indian language)
Ordered-Neurons
Code for the paper "Ordered Neurons: Integrating Tree Structures into Recurrent Neural Networks"
Provable-Data-Subset-Selection-For-Efficient-Neural-Network-Training
Provable Data Subset Selection For Efficient Neural Network Training
Recurrent-Independent-Mechanisms
Implementation of the paper Recurrent Independent Mechanisms (https://arxiv.org/pdf/1909.10893.pdf)
rethinking-network-pruning
Rethinking the Value of Network Pruning (Pytorch) (ICLR 2019)
rnn-hierarchical-biases
Code for "Does syntax need to grow on trees? Sources of inductive bias in sequence to sequence networks"
slimmable_networks
Slimmable Networks, AutoSlim, and Beyond, ICLR 2019, and ICCV 2019