Fair Off-Policy Learning from Observational Data.
|
ICML |
2024 |
0 |
Meta-Learners for Partially-Identified Treatment Effects Across Multiple Environments.
|
ICML |
2024 |
0 |
Causal Machine Learning for Cost-Effective Allocation of Development Aid.
|
KDD |
2024 |
0 |
DiffPO: A causal diffusion model for learning distributions of potential outcomes.
|
NIPS/NeurIPS |
2024 |
0 |
Quantifying Aleatoric Uncertainty of the Treatment Effect: A Novel Orthogonal Learner.
|
NIPS/NeurIPS |
2024 |
0 |
A Neural Framework for Generalized Causal Sensitivity Analysis.
|
ICLR |
2024 |
0 |
Bayesian Neural Controlled Differential Equations for Treatment Effect Estimation.
|
ICLR |
2024 |
0 |
Causal Fairness under Unobserved Confounding: A Neural Sensitivity Framework.
|
ICLR |
2024 |
0 |
Bounds on Representation-Induced Confounding Bias for Treatment Effect Estimation.
|
ICLR |
2024 |
0 |
Leveraging driver vehicle and environment interaction: Machine learning using driver monitoring cameras to detect drunk driving.
|
CHI |
2023 |
0 |
Estimating Average Causal Effects from Patient Trajectories.
|
AAAI |
2023 |
0 |
Normalizing Flows for Interventional Density Estimation.
|
ICML |
2023 |
0 |
DSG: An End-to-End Document Structure Generator.
|
ICDM |
2023 |
0 |
Estimating Conditional Average Treatment Effects with Missing Treatment Information.
|
AISTATS |
2023 |
0 |
Sharp Bounds for Generalized Causal Sensitivity Analysis.
|
NIPS/NeurIPS |
2023 |
0 |
Partial Counterfactual Identification of Continuous Outcomes with a Curvature Sensitivity Model.
|
NIPS/NeurIPS |
2023 |
0 |
Reliable Off-Policy Learning for Dosage Combinations.
|
NIPS/NeurIPS |
2023 |
0 |
Contrastive Learning for Unsupervised Domain Adaptation of Time Series.
|
ICLR |
2023 |
0 |
Estimating individual treatment effects under unobserved confounding using binary instruments.
|
ICLR |
2023 |
0 |
Detecting False Rumors from Retweet Dynamics on Social Media.
|
WWW |
2022 |
12 |
Causal Transformer for Estimating Counterfactual Outcomes.
|
ICML |
2022 |
12 |
Interpretable Off-Policy Learning via Hyperbox Search.
|
ICML |
2022 |
1 |
A Deep Markov Model for Clickstream Analytics in Online Shopping.
|
WWW |
2022 |
4 |
QA Domain Adaptation using Hidden Space Augmentation and Self-Supervised Contrastive Adaptation.
|
EMNLP |
2022 |
0 |
Generalizing off-policy learning under sample selection bias.
|
UAI |
2022 |
0 |
Predicting COVID-19 Spread from Large-Scale Mobility Data.
|
KDD |
2021 |
13 |
Contrastive Domain Adaptation for Question Answering using Limited Text Corpora.
|
EMNLP |
2021 |
13 |
AttDMM: An Attentive Deep Markov Model for Risk Scoring in Intensive Care Units.
|
KDD |
2021 |
14 |
DocParser: Hierarchical Document Structure Parsing from Renderings.
|
AAAI |
2021 |
3 |
Estimating Average Treatment Effects via Orthogonal Regularization.
|
CIKM |
2021 |
24 |
Cascade-LSTM: A Tree-Structured Neural Classifier for Detecting Misinformation Cascades.
|
KDD |
2020 |
17 |
One Picture Is Worth a Thousand Words? The Pricing Power of Images in e-Commerce.
|
WWW |
2020 |
6 |
Sample Complexity Bounds for RNNs with Application to Combinatorial Graph Problems (Student Abstract).
|
AAAI |
2020 |
2 |
Early Detection of User Exits from Clickstream Data: A Markov Modulated Marked Point Process Model.
|
WWW |
2020 |
21 |
Mining Points-of-Interest for Explaining Urban Phenomena: A Scalable Variational Inference Approach.
|
WWW |
2020 |
0 |
Learning a Cost-Effective Annotation Policy for Question Answering.
|
EMNLP |
2020 |
7 |
IntKB: A Verifiable Interactive Framework for Knowledge Base Completion.
|
COLING |
2020 |
6 |
Learning from On-Line User Feedback in Neural Question Answering on the Web.
|
WWW |
2019 |
18 |
Personalized Purchase Prediction of Market Baskets with Wasserstein-Based Sequence Matching.
|
KDD |
2019 |
7 |
RankQA: Neural Question Answering with Answer Re-Ranking.
|
ACL |
2019 |
30 |
Adaptive Document Retrieval for Deep Question Answering.
|
EMNLP |
2018 |
49 |