Merge pull request #3 from VectorInstitute/feature/add-ref-impl-2022-2023

Add reference implementations from years 2022-2023

Author: AnanyaRaval

README.md

@@ -11,6 +11,18 @@
 | [SSGVQAP][ssgvap-repo] | This repository contains code for the paper [A Smart System to Generate and Validate Question Answer Pairs for COVID-19 Literature][ssgvap-paper] which was accepted ibn ACL'20. Authors are Rohan Bhambhoria, Luna Feng, Dawn Sepehr, John Chen, Conner Cowling, Sedef Kocak, Elham Dolatabadi. | An Active Learning Strategy for Data Selection, AL-Uncertainty, AL-Clustering | 1 | [CORD-19] |
 | [NeuralKernelBandits][nkb-repo] | This repository contains code for the paper [An Empirical Study of Neural Kernel Bandits][nkb-paper] which was accepted in Neurips'21. Authors are Lisicki, Michal, Arash Afkanpour, and Graham W. Taylor. | Neural tangent kernel, Conjugate kernel, NNGP, Deep ensembles, Randomized Priors, NTKGP, Upper Confidence Bounds (UCB), Thompson Sampling (TS) | 7 | [Mushroom], [Statlog] <br> [Adult][adult-nkb], [US Census 1990] <br> [Covertype] |
 | [foodprice-forecasting][fpf-repo] | This repository replicates the experiments described on pages 16 and 17 of the [2022 Edition of Canada's Food Price Report][fpf-paper]. | Time series forecasting using Prophet,  Time series forecasting using Neural prophet, Interpretable time series forecasting using N-BEATS, Ensemble of the above methods. | 3 | [FRED Economic Data] |
+| [Recommendation Systems][recsys-repo] | This repository contains demos for various RecSys techniques such as Collaborative Filtering, Knowledge Graph, RL based, Sequence Aware, Session based etc. | SVD++, NeuMF, Plot based, Two tower, SVD, KG based, SlateQ, BST, Simple Association Rules, first-order Markov Chains, Sequential Rules, RNN, Neural Attentive Session, BERT4rec, A2SVDModel, SLi-Rec | 7 | [Amazon-recsys] ,[careervillage], <br> [movielens-recsys], [tmdb], [LastFM] <br> [yoochoose] |
+| [Forecasting with Deep Learning][forecasting-dl-repo] | This repository contains demos for a variety of forecasting techniques for Univariate and Multivariate time series, spatiotemporal forecasting etc. | Exponential Smoothing, Persistence Forecasting,  Mean Window Forecast,  Prophet, Neuralphophet, NBeats, DeepAR, Autoformer, DLinear, NHITS | 11 | [Canadian Weather Station Data], [BoC Exchange rate], [Electricity Consumption], [Road Traffic Occupancy], [Influenza-Like Illness Patient Ratios], [Walmart M5 Retail Product Sales], [WeatherBench], [Grocery Store Sales], [Economic Data with Food CPI] |
+| [Prompt Engineering][pe-repo] |  This repository contains demos for a variety of Prompt Engineering techniques such as fairness measurement via sentiment analysis, finetuning, prompt tuning, prompt ensembling etc. | Bias Quantification & Probing, Stereotypical Bias Analysis, Binary sentiment analysis task, Finetuning using HF Library, Gradient-Search for Instruction Prefix, GRIPS for Instruction Prefix, LLM Summarization, LLM Classification: AG News task, LLM BoolQ (Boolean question answering), LLM Basic Translation (French -> English), LLM Aspect-Based Sentiment Analysis, prompt-tuning, Activation Computation, LLM Classifier Training, Voting and Averaging Ensembles | 10 | [Crow-pairs], [sst5], [cnn_dailymail], [ag_news], [Tweet-data], [Other] |
+| [ABSA][absa-repo] | This repository contains code for the paper [Open Aspect Target Sentiment Classification with Natural Language Prompts][absa-paper]. <br> Authors are Ronald Seoh, Ian Birle, Mrinal Tak, Haw-Shiuan Chang, Brian Pinette, Alfred Hough. | Zero-shot inference for sentiment using PLM and openprompt, Few-shot inference for sentiment using PLM, Zero-shot ATSC with Prompts using BERT and OPT, Zero-shot inference of aspect term and generate sentiment polarity using NLTK pipeline | 4 | [Link][Link-absa] |
+| [NAA][naa-repo] | This repository contains code for the paper [Bringing the State-of-the-Art to Customers: A Neural Agent Assistant Framework for Customer Service Support].[naa-paper] Authors are Stephen Obadinma, Faiza Khan Khattak, Shirley Wang, Tania Sidhorn, Elaine Lau, Sean Robertson, Jingcheng Niu, Winnie Au, Alif Munim, Karthik Raja Kalaiselvi Bhaskar. | Context Retreival using SBERT bi-encoder, Context Retreival using SBERT cross-encoder, Intent identification using BERT, Few Shot Multi-Class Text Classification with BERT, Multi-Class Text Classification with BERT, Reponse generation via GPT2. | 5 | [ELI5],  [MSMARCO] |
+| [Anomaly Detection Project][anomaly-repo] | This repository contains demos for various supervised and unsupervised anomaly detection techniques in domains such as Fraud Detection, Network Intrusion Detection, System Monitoring and image, Video Analysis. | AMNet, GCN, SAGE, OCGNN, DON, AdONE, MLP, FTTransformter, DeepSAD, XGBoost, CBLOF, CFA for Target-Oriented Anomaly Localization, Draem for surface anomaly detection, Logistic Regression, CATBoost,  Random Forest, Diversity Measurable Anomaly Detection, Two-stream I3D Convolutional Network, DeepCNN, CatBoost, LighGBM, Isolation Forest, TabNet, AutoEncoder, Internal Contrastive Learning | 5 | [On Vector Cluster][cluster-anomaly] |
+| [SSL Bootcamp][ssl-repo] | This repository contains demos for self-supervised techniques such as contrastive learning, masked modeling and self distillation. | Internal Contrastive Learning, LatentOD-AD, TabRet,SimMTM, Data2Vec | 52 | [Beijing Air Quality][baq-ssl], [BRFSS][brfss-ssl], [Stroke Prediction][stroke-ssl], [STL10][stl-10-ssl], [Link1][Link1-ssl], [Link2][Link2-ssl]
+| [Causal Inference Lab][ci-lab-repo] |  This repository contains code to estimate the causal effects of an intervention on some measurable outcome primarily in the health domain. | Naive ATE, TARNet, DragonNet, Double Machine Learning, T Learner, S Learner, Inverse Propensity based Learner, PEHE, MAE; Evaluation metrics: R Score, DR Score, Tau Risk, Tau IPTW Score, Tau DR Score, Tau S Score, Tau T Risk, Influence Score | 5 | [Infant Health and Development Program][IHDP], <br> [Jobs], [Twins], <br> [Berkeley admission], <br> [Government Census], [Compas] |
+| [VariationalNeuralAnnealing][vna-repo] | This repository contains code for the paper [Variational neural annealing][vna-paper]. Authors are Mohamed Hibat-Allah, Estelle M. Inack, Roeland Wiersema, Roger G. Melko & Juan Carrasquilla. | Variational neural annealing; Variational Classical Annealing (VCA), Variational Quantum Annealing, Regularized VQA, Classical-Quantum Optimization | 2 | [Edwards-Anderson][EA], [Sherrington-Kirkpatrick][SK] |
+| [HV-Ai-C][hvaic-repo] | This repository implements a Reinforcement Learning agent to optimize energy consumption within Data Centers. | RL agents performing Random action, Fixed action, Q Learning; Hyperspace Neighbor Penetration | - | - |
+| [Flex Model][flex-model-repo] | This repository contains code for the paper [FlexModel: A Framework for Interpretability of Distributed Large Language Models][flex-model-paper]. Authors are Matthew Choi, Muhammad Adil Asif, John Willes, David Emerson.| Distributed Interpretability | - | - |
+| [VBLL][vbll-repo] | This repository contains code for the paper [Variational Bayesian Last Layers][vbll-paper]. Authors are James Harrison, John Willes, Jasper Snoek. | Variational Bayesian Last Layers | 2 | [MNIST], [FashionMNIST]
 --------
 
 [//]: # (Reference links for Github repositories)
@@ -21,13 +33,31 @@
 [ssgvap-repo]: https://github.com/VectorInstitute/SSGVQAP
 [nkb-repo]: https://github.com/VectorInstitute/NeuralKernelBandits
 [fpf-repo]: https://github.com/VectorInstitute/foodprice-forecasting
+[recsys-repo]: https://github.com/VectorInstitute/recommender_systems_project
+[forecasting-dl-repo]: https://github.com/VectorInstitute/forecasting-with-dl
+[pe-repo]: https://github.com/VectorInstitute/PromptEngineering
+[fastgan-repo]: https://github.com/VectorInstitute/FastGAN-pytorch
+[absa-repo]: https://github.com/VectorInstitute/ABSA
+[naa-repo]: https://github.com/VectorInstitute/NAA
+[anomaly-repo]: https://github.com/VectorInstitute/anomaly-detection-project
+[ssl-repo]: https://github.com/VectorInstitute/SSL-Bootcamp
+[ci-lab-repo]: https://github.com/VectorInstitute/Causal_Inference_Laboratory
+[vna-repo]: https://github.com/VectorInstitute/VariationalNeuralAnnealing
+[covid-repo]: https://github.com/VectorInstitute/ProjectLongCovid-NER
+[hvaic-repo]: https://github.com/VectorInstitute/HV-Ai-C
+[flex-model-repo]: https://github.com/VectorInstitute/flex_model
+[vbll-repo]: https://github.com/VectorInstitute/vbll
 
 [//]: # (Reference links for Research papers)
 [laftr-paper]: https://arxiv.org/abs/1802.06309
 [god-paper]: http://proceedings.mlr.press/v119/sastry20a.html
 [ssgvap-paper]: https://aclanthology.org/2020.sdp-1.4/
 [nkb-paper]: https://arxiv.org/abs/2111.03543
 [fpf-paper]: https://www.dal.ca/sites/agri-food/research/canada-s-food-price-report-2022.html
+[absa-paper]: https://aclanthology.org/2021.emnlp-main.509/
+[vna-paper]: https://www.nature.com/articles/s42256-021-00401-3
+[flex-model-paper]: https://arxiv.org/abs/2312.03140
+[vbll-paper]: https://arxiv.org/abs/2404.11599
 
 [//]: # (Reference links for datasets)
 [CIFAR10]: https://pytorch.org/vision/main/generated/torchvision.datasets.CIFAR10.html#torchvision.datasets.CIFAR10
@@ -56,4 +86,46 @@
 [Adult-nkb]: https://archive.ics.uci.edu/dataset/2/adult
 [US Census 1990]: https://archive.ics.uci.edu/dataset/116/us+census+data+1990
 [Covertype]: https://archive.ics.uci.edu/dataset/31/covertype
-[FRED Economic Data]: https://fred.stlouisfed.org/
+[FRED Economic Data]: https://fred.stlouisfed.org/
+[Amazon-recsys]: https://drive.google.com/drive/folders/1w9ofYRBZN5XIb8M-UzbU3Wp4H1ZBYOFi?usp=drive_link
+[careervillage]: https://drive.google.com/drive/folders/1rNeBtNYM7Z0oHVho75PDEP3VZIXAoxx9?usp=drive_link
+[movielens-recsys]: https://drive.google.com/drive/folders/112OtYq83WZgVqV43pGhKZjVTzlUhKM-b?usp=drive_link
+[tmdb]: https://drive.google.com/drive/folders/1CU863OynVNnNTTduKxExubCyJLCZPF0R?usp=drive_link
+[LastFM]: https://drive.google.com/drive/folders/1Jftz1_olxblJVZe6ZDMdrclAW_YnCOci?usp=drive_link
+[yoochoose]: https://drive.google.com/drive/folders/1XNyPH8i-pxnNbJKjZZRCL1oz-HPZscLC?usp=drive_link
+[Canadian Weather Station Data]: https://drive.google.com/drive/folders/1YeOoJNf7VCy7r3sFhdTrl7WdevcUIZNW
+[BoC Exchange rate]: https://drive.google.com/drive/folders/1Z9pnC0kPN-c_eAHSsPyWPYRnnGR3sEuf
+[Electricity Consumption]: https://drive.google.com/drive/folders/1YIl6RHAQ5muZEjFjXLj7Zt4vOwKUu2Qe
+[Road Traffic Occupancy]: https://drive.google.com/drive/folders/1YDM-mMGuhlE_pTlwb5qoPcOQfspJ4m4W
+[Influenza-Like Illness Patient Ratios]: https://drive.google.com/drive/folders/1YFoC3fWY-22S11MtfKHnl_R8OminZ2eo
+[Walmart M5 Retail Product Sales]: https://drive.google.com/drive/folders/1bc488T1GsJ3xg2nQmuFTut7uF1SFDSp2
+[WeatherBench]:https://drive.google.com/drive/folders/1YD-Hadx_T4JZcjmvFYDp4Pb71852CIVT
+[Grocery Store Sales]: https://drive.google.com/drive/folders/1as_cJgJbzw1OlnWyF8Y3xj7ZEjRh_kD6
+[Economic Data with Food CPI]: https://drive.google.com/drive/folders/1cNyHR5DpUQ5RORgDS8pB8iswWo-iBLFI
+[Crow-pairs]: https://github.com/VectorInstitute/PromptEngineering/blob/main/src/reference_implementations/fairness_measurement/crow_s_pairs/resources/crows_pairs_anonymized.csv
+[sst5]: http://github.com/VectorInstitute/PromptEngineering/blob/main/src/reference_implementations/fairness_measurement/czarnowska_analysis/resources/processed_sst5.tsv
+[cnn_dailymail]: https://huggingface.co/datasets/ccdv/cnn_dailymail
+[ag_news]: https://huggingface.co/datasets/fancyzhx/ag_news
+[Tweet-data]: https://github.com/VectorInstitute/PromptEngineering/tree/main/resources/datasets
+[Other]: https://github.com/VectorInstitute/PromptEngineering/tree/main/src/reference_implementations/prompting_vector_llms/llm_prompting_examples/resources
+[Few shot images dataset]: https://drive.google.com/file/d/1aAJCZbXNHyraJ6Mi13dSbe7pTyfPXha0/view
+[Link-absa]: https://github.com/VectorInstitute/ABSA/tree/main/atsc_paper/atsc_prompts_modified/dataset_files
+[ELI5]: https://drive.google.com/drive/folders/1PDBiij-6JSxOtplOSc0hPTk9zL9n3qR6
+[MSMARCO]: https://drive.google.com/drive/folders/1LO3OtuDC_FSFktTgb2NfjPY2cse7WcTY
+[cluster-anomaly]: https://github.com/VectorInstitute/anomaly-detection-project/tree/main?tab=readme-ov-file#datasets
+[baq-ssl]: https://zenodo.org/records/3902671
+[brfss-ssl]: https://www.cdc.gov/brfss/
+[stroke-ssl]: https://www.kaggle.com/datasets/fedesoriano/stroke-prediction-dataset
+[stl-10-ssl]: https://cs.stanford.edu/~acoates/stl10/
+[Link1-ssl]: https://github.com/VectorInstitute/SSL-Bootcamp/tree/main/contrastive_learning/ICL/datasets/Classical
+[Link2-ssl]: https://github.com/VectorInstitute/SSL-Bootcamp/tree/main/contrastive_learning/LatentOE/DATA
+[IHDP]: https://github.com/VectorInstitute/Causal_Inference_Laboratory/tree/main/data/IHDP-100
+[Jobs]: https://github.com/VectorInstitute/Causal_Inference_Laboratory/tree/main/data/Jobs
+[Twins]: https://github.com/VectorInstitute/Causal_Inference_Laboratory/tree/main/data/TWINS
+[Berkeley admission]: https://github.com/VectorInstitute/Causal_Inference_Laboratory/tree/main/data/CFA
+[Government Census]: https://github.com/VectorInstitute/Causal_Inference_Laboratory/tree/main/data/CFA 
+[Compas]: https://github.com/VectorInstitute/Causal_Inference_Laboratory/tree/main/data/CFA
+[EA]: https://github.com/VectorInstitute/VariationalNeuralAnnealing/tree/main/data/EA
+[SK]: https://github.com/VectorInstitute/VariationalNeuralAnnealing/tree/main/data/SK
+[MNIST]: https://huggingface.co/datasets/ylecun/mnist
+[FashionMNIST]: https://huggingface.co/datasets/zalando-datasets/fashion_mnist