sarthak-chakraborty

shap

A game theoretic approach to explain the output of any machine learning model.

iperf

iperf3: A TCP, UDP, and SCTP network bandwidth measurement tool

pytorch-seq2seq

Tutorials on implementing a few sequence-to-sequence (seq2seq) models with PyTorch and TorchText.

FedML

FEDML - The unified and scalable ML library for large-scale distributed training, model serving, and federated learning. FEDML Launch, a cross-cloud scheduler, further enables running any AI jobs on any GPU cloud or on-premise cluster. Built on this library, TensorOpera AI (https://TensorOpera.ai) is your generative AI platform at scale.

Conference-Acceptance-Rate

Acceptance rates for the major AI conferences

microservices-demo

Deployment scripts & config for Sock Shop

causal-learn

Causal Discovery in Python. It also includes (conditional) independence tests and score functions.

Seq2Seq-PyTorch

Sequence to Sequence Models with PyTorch

DeathStarBench

Open-source benchmark suite for cloud microservices

train-ticket

Train Ticket - A Benchmark Microservice System

FedProx

Federated Optimization in Heterogeneous Networks (MLSys '20)

METIS

METIS - Serial Graph Partitioning and Fill-reducing Matrix Ordering

Awesome-LLM-Uncertainty-Reliability-Robustness

Awesome-LLM-Robustness: a curated list of Uncertainty, Reliability and Robustness in Large Language Models

tetrad

Repository for the Tetrad Project, www.phil.cmu.edu/tetrad.

DeepCCA

An implementation of Deep Canonical Correlation Analysis (DCCA or Deep CCA) with pytorch.

fair_flearn

Fair Resource Allocation in Federated Learning (ICLR '20)

FedBN

[ICLR'21] FedBN: Federated Learning on Non-IID Features via Local Batch Normalization

azure-kusto-python

Kusto client libraries for Python

CRISP

RCAPapers

Papers about Root Cause Analysis in MicroService Systems. Reference to Paper Notes: https://dreamhomes.top/

Deep-Clustering-Network

PyTorch Implementation of "Towards K-Means-Friendly Spaces: Simultaneous Deep Learning and Clustering," Bo Yang et al., ICML'2017.

mlb-youtube

MLB-YouTube dataset, code and models for fine-grained activity recognition (CVsports 2018)

hmm_for_autonomous_driving

🎓 Educational application of Hidden Markov Model to Autonomous Driving 🚕🚙🚗

RecursiveHierarchicalClustering

Use iterative feature pruning to identify hierarchical clusters.

TorchCoder

PyTorch based autoencoder for sequential data

hidden-markov-model

A from-scratch Hidden Markov Model for hidden state learning from observation sequences.

rcd

Root Cause Discovery: Root Cause Analysis of Failures in Microservices through Causal Discovery

autothrottle

Codebase for Autothrottle (NSDI 2024)

FedML-Mobile

FedML-Mobile: Federated Learning Research Library for Android and iOS Smartphones (supported by FedML framework)

DeepScaler