Aditya Golatkar's repositories
Classification-of-Breast-Cancer-Histology-using-Deep-Learning
Our solution to the BACH challenge organised by ICIAR 2018. Also contains our paper which was published at the conference
Sentence-Summarization-using-LSTMs
Keras implementation of bi-LSTMs for sentence summarization. Obtained better marginally better results than a work by Google on same topic. CS 726 IIT Bombay project
Sparse-Kernel-PCA-for-outlier-detection
Our codes and results for our work on SKPCA for outlier detection.
Exemplar-Based-Inpainting
Exemplar Based Inpainting
Algorithms-for-medical-image-processing-IIT-Bombay
Our implementation of course assignments and the course project.
Document-Summarization-by-key-sentence-extraction-using-NN
Codes and reports of the Foundations Machine Learning (CS 403 IIT Bombay) course project.
Existence-of-sparse-basis-for-deep-learning-kernels
Deep Neural Networks for Sparse KPCA
over-parametrization
Computing various norms/measures on over-parametrized neural networks
RL-Adventure
Pytorch Implementation of DQN / DDQN / Prioritized replay/ noisy networks/ distributional values/ Rainbow/ hierarchical RL
AdityaGolatkar
Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes
all-conv-pytorch
Pytorch implementation of "Striving for Simplicity: The All Convolutional Net" (https://arxiv.org/abs/1412.6806)
Digital-Image-Processing-IIT-Bombay
Codes for DIP course (CS 663) IIT Bombay
MAML-Pytorch
Elegant PyTorch implementation of paper Model-Agnostic Meta-Learning (MAML)
Microprocessor-Lab-IIT-Bombay
Codes for Microprocessor Lab at IIT Bombay
Microprocessor-Lab-Project-IIT-Bombay
Codes along with describing images for Microprocessor Lab Project IIT Bombay
MINE-Mutual-Information-Neural-Estimation-
A pytorch implementation of MINE(Mutual Information Neural Estimation)
Nystrom-method-to-speed-KPCA
Implementation of our algorithm which has improved time complexity (linear speed up) for KPCA over MATLAB's eig function.
pytorch-seq2seq
Tutorials on implementing a few sequence-to-sequence (seq2seq) models with PyTorch and TorchText. [IN PROGRESS]
vision
Datasets, Transforms and Models specific to Computer Vision