Do You Even Need Attention? A Stack of Feed-Forward Layers Does Surprisingly Well on ImageNet

Github: https://github.com/lukemelas/do-you-even-need-attention

Paper: https://arxiv.org/abs/2105.02723
👉 @bigdata_1

DensePhrases is an extractive phrase search tool based on your natural language inputs

Github: https://github.com/princeton-nlp/DensePhrases

Paper: https://arxiv.org/abs/2109.08133v1

Dataset: https://paperswithcode.com/dataset/squad
👉 @bigdata_1

Deep Implicit Attention: A Mean-Field Theory Perspective on Attention Mechanisms

https://mcbal.github.io/post/deep-implicit-attention-a-mean-field-theory-perspective-on-attention-mechanisms/

👉 @bigdata_1

☄️ Uncertainty-Aware Machine Translation Evaluation

Code: https://github.com/Unbabel/COMET

Paper: https://arxiv.org/abs/2109.06352v1

Documentation: https://unbabel.github.io/COMET/html/index.html
👉 @bigdata_1

Two4Two: Evaluating Interpretable Machine Learning -- A Synthetic Dataset For Controlled Experiments

Github: https://github.com/mschuessler/two4two

Paper: https://arxiv.org/abs/2105.02825v1
👉 @bigdata_1

🌳 WildWood: a new Random Forest algorithm

Github: https://github.com/pyensemble/wildwood

Paper: https://arxiv.org/abs/2109.08010v1

Documentation: https://wildwood.readthedocs.io/
👉 @bigdata_1

Body Meshes as Points

Github: https://github.com/jfzhang95/BMP

Paper: https://arxiv.org/abs/2105.02467v1
👉 @bigdata_1

Chimera: Learning Shared Semantic Space for Speech-to-Text Translation (Nightly Version)

Github: https://github.com/Glaciohound/Chimera-SLT

Paper: https://arxiv.org/abs/2105.03095

👉 @bigdata_1

📄 Revisiting Mask-Head Architectures for Novel Class Instance Segmentation

https://ai.googleblog.com/2021/09/revisiting-mask-head-architectures-for.html

DeepMAC model: https://github.com/tensorflow/models/blob/master/research/object_detection/g3doc/deepmac.md

Paper: https://arxiv.org/abs/2104.00613

👉 @bigdata_1

⚽️ Advancing sports analytics through AI research

🔥 Deepmind blog : https://deepmind.com/blog/article/advancing-sports-analytics-through-ai

A Dataset and Benchmarks: https://soccer-net.org/

Dataset: https://github.com/statsbomb/open-data

Paper: https://sites.google.com/view/ijcai-aisa-2021/

👉 @bigdata_1

Simple Entity-Centric Questions Challenge Dense Retrievers

Github: https://github.com/princeton-nlp/entityquestions

Paper: https://arxiv.org/abs/2109.08535v1

Dataset: https://paperswithcode.com/dataset/natural-questions

👉 @bigdata_1

Diffusion Models Beat GANs on Image Synthesis

Github: https://github.com/openai/guided-diffusion

Paper: https://arxiv.org/abs/2105.05233v1

👉 @bigdata_1

The Machine & Deep Learning Compendium Open Book

https://book.mlcompendium.com/

GitBook: https://github.com/orico/www.mlcompendium.com

👉 @bigdata_1

Self-Supervised Learning with Swin Transformers

Github: https://github.com/SwinTransformer/Transformer-SSL

Paper: https://arxiv.org/abs/2105.04553v2

👉 @bigdata_1

Dynamic Slimmable Network (DS-Net)

Github: https://github.com/M3DV/AlignShift

Paper: https://arxiv.org/abs/2109.10060v1

👉 @bigdata_1

A Large-Scale Benchmark for Food Image Segmentation

Github: https://github.com/XiongweiWu/FoodSeg-Benchmark

Paper: https://arxiv.org/abs/2105.05409v1

👉 @bigdata_1

Language Models are Few-shot Multilingual Learners

Github: https://github.com/gentaiscool/few-shot-lm

Paper: https://arxiv.org/abs/2109.07684v1

👉 @bigdata_1

EL-Attention: Memory Efficient Lossless Attention for Generation

Github: https://github.com/microsoft/fastseq

Paper: https://arxiv.org/abs/2105.04779v1

👉 @bigdata_1

CompilerGym: Robust, Performant Compiler Optimization Environments for AI Research

CompilerGym is a library of easy to use and performant reinforcement learning environments for compiler tasks.

Github: https://github.com/facebookresearch/CompilerGym

Documents: https://facebookresearch.github.io/CompilerGym/

Paper: https://arxiv.org/abs/2109.08267v1

👉 @bigdata_1

SyntheticFur Dataset Description

Gitgub: https://github.com/google-research-datasets/synthetic-fur

Paper: https://arxiv.org/abs/2105.06409

Video: https://youtu.be/5uraQu_5Tyg

👉 @bigdata_1