Collection of must read papers for Data Science, or Machine Learning / Deep Learning Engineer

A curated list of the most impressive AI papers

Text and code for the second edition of Think Bayes, by Allen Downey.

Jupyter notebooks and other resources for Think Python by Allen Downey, published by O'Reilly Media.

[ECCV 2020] ScanRefer: 3D Object Localization in RGB-D Scans using Natural Language

Python package for importing and loading external assets into AI2THOR

Explain, analyze, and visualize NLP language models. Ecco creates interactive visualizations directly in Jupyter notebooks explaining the behavior of Transformer-based language models (like GPT2, B…

Differentiable Scan Context with Orientation

The easiest way to use deep metric learning in your application. Modular, flexible, and extensible. Written in PyTorch.

A Simple Baseline for BEV Perception

Word Mover's Distance from Matthew J Kusner's paper "From Word Embeddings to Document Distances"

a Realistic and Rich 3D Environment

LightGlue: Local Feature Matching at Light Speed (ICCV 2023)

Lift, Splat, Shoot: Encoding Images from Arbitrary Camera Rigs by Implicitly Unprojecting to 3D (ECCV 2020)

[ICLR 2021, Spotlight] Large Scale Image Completion via Co-Modulated Generative Adversarial Networks

Some papers that have been of great help in my work, especially in the fields of ML and DL.

Localization via embodied dialog on the navigation graph

Repository of our accepted NeurIPS-2022 paper "Towards Versatile Embodied Navigation"

[ECCV2024] Video Foundation Models & Data for Multimodal Understanding

Hypersim: A Photorealistic Synthetic Dataset for Holistic Indoor Scene Understanding

Official implementation of "Decoder Modulation for Indoor Depth Completion" https://arxiv.org/abs/2005.08607

MATLAB script that converts equirectangular images into six cube faces

Repository for "Behavioral Analysis of Vision-and-Language Navigation Agents" (CVPR 2023)