tufts-ml/Reading-List

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tufts-ml/Reading-List

tufts-ml

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graph-generation-EDGE

EDGE: Efficient and Degree-Guided Graph Generation via Discrete Diffusion Modeling

GAN-Ensemble-for-Anomaly-Detection

This repository is the PyTorch implementation of GAN Ensemble for Anomaly Detection.

KCN

Kriging Convolutional Networks (KCN) in Tensoflow

graph-generation-vi

This repository contains PyTorch implementation of the following paper: "Order Matters: Probabilistic Modeling of Node Sequence for Graph Generation"

fNIRS-mental-workload-classifiers

Code for training, evaluating, and visualizing performance of mental workload classification using fNIRS BCI sensors

Jupyter Notebook

kcn-torch

Jupyter Notebook

SSL-vs-SSL-benchmark

Code for benchmark comparing self-supervised and semi-supervised deep classifiers for medical images

ssl-for-echocardiograms

Code for the MLHC 2021 paper: A New Semi-supervised Learning Benchmark for Classifying View and Diagnosing Aortic Stenosis from Echocardiograms

time_series_prediction

Code for prediction given sequential data with some missing / irregularly-spaced values (PI: Mike Hughes).

Jupyter Notebook

Prune4SED

fix-a-step

Code for semi-supervised learning using Fix-A-Step

PatchGT

This repository contains PyTorch implementation of the submission: PatchGT: Transformer over Non-trainable Clusters for Learning Graph Representations

sigma

false-alarm-control

Code for training binary classifiers to maximize recall subject to a minimum precision constraint. Paper published at AISTATS '22.

Jupyter Notebook

tmed2-echocardiogram-classifiers

Code for classification of echocardiograms (view type, severity level) with the TMED dataset

Jupyter Notebook

Graph-Generation-MLE

cumulative-link-models

Code for cumulative link models for ordinal regression that support differentiable learning ala PyTorch

categorical-from-binary

Code for the paper "Easy Variational Inference for Categorical Models via an Independent Binary Approximation"

single-hospital-count-forecasting

Methods to forecast counts of hospital utilization at a single hospital site during COVID-19 pandemic.

Jupyter Notebook

covid19-forecasting

Simulation software for forecasting demand at various stages of hospitalization

SepNorm

Jupyter Notebook

aigp

The code for the inference method, AIGP, for Gaussian Processes

comp150_bdl_2018f_public

Public code repo for Tufts COMP 150-03 in Fall 2018

Jupyter Notebook

SAMIL

Code for the paper Detecting Heart Disease from Multi-View Ultrasound Images via Supervised Attention Multiple Instance Learning

pchmm-missing-data-limited-labels

Repository for paper "Prediction-Constrained Markov Models for Medical Time Series with Missing Data and Few Labels" at NeurIPS workshop (Learning from Time Series For Health)

Jupyter Notebook

any_parameter_encoder

Public code release accompanying the AABI 2019 paper "Rapid Model Comparison by Amortizing Across Models" by Lily H. Zhang and Michael C. Hughes

aced-hmm-hospitalized-patient-trajectory-model

Code for a model of how COVID-19 patients progress through stages of care in the hospital. Includes ability to forecast from the model, as well as simulation-based inference.

Jupyter Notebook

tufts_ml_website

Source code for the Tufts ML website

InterLUDE

Code for ICML 2024 paper "InterLUDE: Interactions between Labeled and Unlabeled Data to Enhance Semi-supervised Learning"

hugheslab-onboarding

Onboarding info for hugheslab (HPC cluster, etc.)

data-driven-missingness-cru-irregular-timeseries

Code for irregular time-series models with missing-not-at-random assumption

Jupyter Notebook

variational-for-mixture-of-gaussians

Demo repository of code and writeup for variational methods for a mixture of Gaussians