Official PyTorch Implementation of Guarding Barlow Twins Against Overfitting with Mixed Samples

PyTorch Implementation of Attention Prompt Tuning: Parameter-Efficient Adaptation of Pre-Trained Models for Action Recognition

[arXiv] "Uncovering the Hidden Cost of Model Compression" by Diganta Misra, Agam Goyal, Bharat Runwal, and Pin-Yu Chen

Exploring and interpreting pretrained deep neural networks.

Official codebase for "Siamese Prototypical Contrastive Learning"

Train a JEPA world model on a set of pre-collected trajectories from a toy environment involving an agent in two rooms.

A framework to compute threshold sensitivity of deep networks to visual stimuli.

In this project, I used CSV module to implement CRUD operations on CSV file using Python Programming Language. The CSV file has over 400,000 records of phone numbers. Searching them linearly may cause a lot of time. Therefore, I used Hash Table to search phone numbers in O(1).

Linear probing of patch-level representations from ViT-based models (CLIP, DINO, MAE...) on a semantic segmentation dataset.

Hash Table, Dictionary, Linear Probing, Unit Testing, Sorting, Quick Sorting, Frequency ranking, ArrayList.

Implementation of Hashing with collision handling, utilizing Chaining, Linear Probing, Quadratic Probing and Double Hashing.