This list is maintained to keep track of the repositories that contain "mirror" versions of the code, e.g. personal repositories of the lab members.
| Paper | Journal/Conference | Code | Mirror Repo(s) URL |
|---|---|---|---|
| Bayesian Inference of Individualized Treatment Effects using Multi-task Gaussian Processes | NIPS 2017 | alg/causal_multitask_gaussian_processes_ite |
N/A |
| Deep Multi-task Gaussian Processes for Survival Analysis with Competing Risks | NIPS 2017 | alg/dgp_survival |
N/A |
| AutoPrognosis: Automated Clinical Prognostic Modeling via Bayesian Optimization with Structured Kernel Learning | ICML 2018 | alg/autoprognosis |
https://github.com/ahmedmalaa/AutoPrognosis |
| Limits of Estimating Heterogeneous Treatment Effects: Guidelines for Practical Algorithm Design | ICML 2018 | alg/causal_multitask_gaussian_processes_ite |
N/A |
| GAIN: Missing Data Imputation using Generative Adversarial Nets | ICML 2018 | alg/gain |
https://github.com/jsyoon0823/GAIN |
| RadialGAN: Leveraging multiple datasets to improve target-specific predictive models using Generative Adversarial Networks | ICML 2018 | alg/RadialGAN |
N/A |
| GANITE: Estimation of Individualized Treatment Effects using Generative Adversarial Nets | ICLR 2018 | alg/ganite |
https://github.com/jsyoon0823/GANITE |
| Deep Sensing: Active Sensing using Multi-directional Recurrent Neural Networks | ICLR 2018 | alg/DeepSensing (MRNN) |
N/A |
| DeepHit: A Deep Learning Approach to Survival Analysis with Competing Risks | AAAI 2018 | alg/deephit |
https://github.com/chl8856/DeepHit |
| INVASE: Instance-wise Variable Selection using Neural Networks | ICLR 2019 | alg/invase |
https://github.com/jsyoon0823/INVASE |
| PATE-GAN: Generating Synthetic Data with Differential Privacy Guarantees | ICLR 2019 | alg/pategan |
N/A |
| KnockoffGAN: Generating Knockoffs for Feature Selection using Generative Adversarial Networks | ICLR 2019 | alg/knockoffgan |
N/A |
| ASAC: Active Sensing using Actor-Critic Models | MLHC 2019 | alg/asac |
N/A |
| Demystifying Black-box Models with Symbolic Metamodels | NeurIPS 2019 | alg/symbolic_metamodeling |
https://github.com/ahmedmalaa/Symbolic-Metamodeling |
| Differentially Private Bagging: Improved Utility and Cheaper Privacy than Subsample-and-Aggregate | NeurIPS 2019 | alg/dpbag |
https://github.com/jsyoon0823/DPBag |
| Time-series Generative Adversarial Networks | NeurIPS 2019 | alg/timegan |
https://github.com/jsyoon0823/TimeGAN |
| Attentive State-Space Modeling of Disease Progression | NeurIPS 2019 | alg/attentivess |
https://github.com/ahmedmalaa/attentive-state-space-models |
| Conditional Independence Testing using Generative Adversarial Networks | NeurIPS 2019 | alg/gcit |
https://github.com/alexisbellot/GCIT |
| Dynamic-DeepHit: A Deep Learning Approach for Dynamic Survival Analysis with Competing Risks based on Longitudinal Data | IEEE | alg/dynamic_deephit |
https://github.com/chl8856/Dynamic-DeepHit |
| Temporal Quilting for Survival Analysis | AISTATS 2019 | alg/survivalquilts |
https://github.com/chl8856/SurvivalQuilts |
| Estimating Counterfactual Treatment Outcomes over Time through Adversarially Balanced Representations | ICLR 2020 | alg/counterfactual_recurrent_network |
https://github.com/ioanabica/Counterfactual-Recurrent-Network |
| Contextual Constrained Learning for Dose-Finding Clinical Trials | AISTATS 2020 | alg/c3t_budgets |
N/A |
| Learning Overlapping Representations for the Estimation of Individualized Treatment Effects | AISTATS 2020 | alg/dklite |
N/A |
| Learning Dynamic and Personalized Comorbidity Networks from Event Data using Deep Diffusion Processes | AISTATS 2020 | alg/dynamic_disease_network_ddp |
N/A |
| Stepwise Model Selection for Sequence Prediction via Deep Kernel Learning | AISTATS 2020 | alg/smsdkl |
N/A |
| Temporal Phenotyping using Deep Predicting Clustering of Disease Progression | ICML 2020 | alg/ac_tpc |
https://github.com/chl8856/AC_TPC |
| Time Series Deconfounder: Estimating Treatment Effects over Time in the Presence of Hidden Confounders | ICML 2020 | alg/time_series_deconfounder |
https://github.com/ioanabica/Time-Series-Deconfounder |
| Discriminative Jackknife: Quantifying Uncertainty in Deep Learning via Higher-Order Influence Functions | ICML 2020 | alg/discriminative-jackknife |
https://github.com/ahmedmalaa/discriminative-jackknife |
| Frequentist Uncertainty in Recurrent Neural Networks via Blockwise Influence Functions | ICML 2020 | alg/rnn-blockwise-jackknife |
https://github.com/ahmedmalaa/rnn-blockwise-jackknife |
| Unlabelled Data Improves Bayesian Uncertainty Calibration under Covariate Shift | ICML 2020 | alg/transductive_dropout |
https://github.com/XanderJC/transductive-dropout |
| Anonymization Through Data Synthesis Using Generative Adversarial Networks (ADS-GAN) | IEEE | alg/adsgan |
N/A |
| When and How to Lift the Lockdown? Global COVID-19 Scenario Analysis and Policy Assessment using Compartmental Gaussian Processes | NeurIPS 2020 | alg/compartmental_gp |
https://github.com/ZhaozhiQIAN/Compartmental-GP-NeurIPS-2020 |
| Strictly Batch Imitation Learning by Energy-based Distribution Matching | NeurIPS 2020 | alg/edm |
https://github.com/danieljarrett/EDM |
| Gradient Regularized V-Learning for Dynamic Treatment Regimes | NeurIPS 2020 | alg/grv |
N/A |
| CASTLE: Regularization via Auxiliary Causal Graph Discovery | NeurIPS 2020 | alg/castle |
https://github.com/trentkyono/CASTLE |
| OrganITE: Optimal transplant donor organ offering using an individual treatment effect | NeurIPS 2020 | alg/organite |
TBC |
| Robust Recursive Partitioning for Heterogeneous Treatment Effects with Uncertainty Quantification | NeurIPS 2020 | alg/r2p-hte |
N/A |
| Estimating the Effects of Continuous-valued Interventions using Generative Adversarial Networks | NeurIPS 2020 | alg/scigan |
https://github.com/ioanabica/SCIGAN |
| Learning outside the Black-Box: The pursuit of interpretable models | NeurIPS 2020 | alg/Symbolic-Pursuit |
https://github.com/JonathanCrabbe/Symbolic-Pursuit |
| VIME: Extending the Success of Self- and Semi-supervised Learning to Tabular Domain | NeurIPS 2020 | alg/vime |
https://github.com/jsyoon0823/VIME |
| Scalable Bayesian Inverse Reinforcement Learning | ICLR 2021 | alg/scalable-birl |
https://github.com/XanderJC/scalable-birl |
| Nonparametric Estimation of Heterogeneous Treatment Effects: From Theory to Learning Algorithms | AISTATS 2021 | alg/CATENets |
https://github.com/AliciaCurth/CATENets |
| Learning Matching Representations for Individualized Organ Transplantation Allocation | AISTATS 2021 | alg/MatchingRep |
https://github.com/CanXu0728/MatchingRep |
| Explaining by Imitating: Understanding Decisions by Interpretable Policy Learning | ICLR 2021 | alg/interpole |
N/A |
| Inverse Decision Modeling: Learning Interpretable Representations of Behavior | ICML 2021 | alg/ibrc |
N/A |
| Policy Analysis using Synthetic Controls in Continuous-Time | ICML 2021 | alg/Synthetic-Controls-in-Continuous-Time |
https://github.com/alexisbellot/Synthetic-Controls-in-Continuous-Time |
| Learning Queueing Policies for Organ Transplantation Allocation using Interpretable Counterfactual Survival Analysis | ICML 2021 | alg/organsync |
https://github.com/jeroenbe/organsync |
| Explaining Time Series Predictions with Dynamic Masks | ICML 2021 | alg/Dynamask |
https://github.com/JonathanCrabbe/Dynamask/ |
| Generative Time-series Modeling with Fourier Flows | ICLR 2021 | alg/Fourier-flows |
https://github.com/ahmedmalaa/Fourier-flows |
| On Inductive Biases for Heterogeneous Treatment Effect Estimation | NeurIPS 2021 | alg/CATENets |
https://github.com/AliciaCurth/CATENets |
| The Medkit-Learn(ing) Environment: Medical Decision Modelling through Simulation | NeurIPS 2021 | alg/medkit-learn |
https://github.com/XanderJC/medkit-learn |
| MIRACLE: Causally-Aware Imputation via Learning Missing Data Mechanisms | NeurIPS 2021 | alg/MIRACLE |
https://github.com/trentkyono/MIRACLE |
| DECAF: Generating Fair Synthetic Data Using Causally-Aware Generative Networks | NeurIPS 2021 | alg/DECAF |
https://github.com/trentkyono/DECAF |
| Explaining Latent Representations with a Corpus of Examples | NeurIPS 2021 | alg/Simplex |
https://github.com/JonathanCrabbe/Simplex |
| Closing the loop in medical decision support by understanding clinical decision-making: A case study on organ transplantation | NeurIPS 2021 | alg/iTransplant |
https://github.com/yvchao/iTransplan |
| Integrating Expert ODEs into Neural ODEs: Pharmacology and Disease Progression | NeurIPS 2021 | alg/Hybrid-ODE-NeurIPS-2021 |
https://github.com/ZhaozhiQIAN/Hybrid-ODE-NeurIPS-2021 |
| SyncTwin: Treatment Effect Estimation with Longitudinal Outcomes | NeurIPS 2021 | alg/SyncTwin-NeurIPS-2021 |
https://github.com/ZhaozhiQIAN/SyncTwin-NeurIPS-2021 |
| Conformal Time-series Forecasting | NeurIPS 2021 | alg/conformal-rnn |
https://github.com/kamilest/conformal-rnn |
| Estimating Multi-cause Treatment Effects via Single-cause Perturbation | NeurIPS 2021 | alg/Single-Cause-Perturbation-NeurIPS-2021 |
https://github.com/ZhaozhiQIAN/Single-Cause-Perturbation-NeurIPS-2021 |
| Invariant Causal Imitation Learning for Generalizable Policies | NeurIPS 2021 | alg/Invariant-Causal-Imitation-Learning |
https://github.com/ioanabica/Invariant-Causal-Imitation-Learning.git |
| Inferring Lexicographically-Ordered Rewards from Preferences | AAAI 2022 | alg/lori |
https://github.com/vanderschaarlab/lori |
| Inverse Online Learning: Understanding Non-Stationary and Reactionary Policies | ICLR 2022 | alg/inverse-online |
https://github.com/vanderschaarlab/inverse-online |
| D-CODE: Discovering Closed-form ODEs from Observed Trajectories | ICLR 2022 | alg/D-CODE-ICLR-2022 |
https://github.com/vanderschaarlab/D-CODE-ICLR-2022 |
| Neural graphical modelling in continuous-time: consistency guarantees and algorithms | ICLR 2022 | alg/Graphical-modelling-continuous-time |
https://github.com/alexisbellot/Graphical-modelling-continuous-time |
| Label-Free Explainability for Unsupervised Models | ICML 2022 | alg/Label-Free-XAI |
https://github.com/vanderschaarlab/Label-Free-XAI |
| Inverse Contextual Bandits: Learning How Behavior Evolves over Time | ICML 2022 | alg/invconban |
https://github.com/vanderschaarlab/invconban |
| Data-SUITE: Data-centric identification of in-distribution incongruous examples | ICML 2022 | alg/Data-SUITE |
https://github.com/seedatnabeel/Data-SUITE |
| Continuous-Time Modeling of Counterfactual Outcomes Using Neural Controlled Differential Equations | ICML 2022 | alg/TE-CDE |
https://github.com/seedatnabeel/TE-CDE |
| Concept Activation Regions: A Generalized Framework For Concept-Based Explanations | NeurIPS 2022 | alg/CARs |
https://github.com/JonathanCrabbe/CARs |
| Benchmarking Heterogeneous Treatment Effect Models through the Lens of Interpretability | NeurIPS 2022 | alg/ITErpretability |
https://github.com/JonathanCrabbe/ITErpretability |
| Transfer Learning on Heterogeneous Feature Spaces for Treatment Effects Estimation | NeurIPS 2022 | alg/HTCE-learners |
https://github.com/ioanabica/HTCE-learners |
| Synthetic Model Combination: An Instance-wise Approach to Unsupervised Ensemble Learning | NeurIPS 2022 | alg/synthetic-model-combination |
https://github.com/XanderJC/synthetic-model-combination |