Greg Ver Steeg

MMG: Mutual Information Estimation via the MMSE Gap in Diffusion UAI 2026 Asymmetric Bias in Text-to-Image Generation with Adversarial Attacks ACL 2024 Ensembled Prediction Intervals for Causal Outcomes Under Hidden Confounding CLeaR 2024 Interpretable Diffusion via Information Decomposition ICLR 2024 Interpretable Measures of Conceptual Similarity by Complexity-Constrained Descriptive Auto-Encoding CVPR 2024 Policy Learning for Localized Interventions from Observational Data AISTATS 2024 Prompt Perturbation Consistency Learning for Robust Language Models EACL 2024 Your Diffusion Model is Secretly a Noise Classifier and Benefits from Contrastive Training NeurIPS 2024 Information-Theoretic Diffusion ICLR 2023 Jointly Reparametrized Multi-Layer Adaptation for Efficient and Private Tuning ACL 2023 Measuring and Mitigating Local Instability in Deep Neural Networks ACL 2023 Neural Architecture Search for Parameter-Efficient Fine-tuning of Large Pre-trained Language Models ACL 2023 Partial identification of dose responses with hidden confounders UAI 2023 Attributing Fair Decisions with Attention Interventions NAACL 2022 Failure Modes of Domain Generalization Algorithms CVPR 2022 Improving Mutual Information Estimation with Annealed and Energy-Based Bounds ICLR 2022 Mitigating Gender Bias in Distilled Language Models via Counterfactual Role Reversal ACL 2022 StATIK: Structure and Text for Inductive Knowledge Graph Completion NAACL 2022 Temporal Generalization for Spoken Language Understanding NAACL 2022 Zero-Shot Cross-Lingual Sequence Tagging as Seq2Seq Generation for Joint Intent Classification and Slot Filling EMNLP 2022 Controllable Guarantees for Fair Outcomes via Contrastive Information Estimation AAAI 2021 Graph Traversal with Tensor Functionals: A Meta-Algorithm for Scalable Learning ICLR 2021 Hamiltonian Dynamics with Non-Newtonian Momentum for Rapid Sampling NeurIPS 2021 Implicit SVD for Graph Representation Learning NeurIPS 2021 Influence Decompositions For Neural Network Attribution AISTATS 2021 Information-theoretic generalization bounds for black-box learning algorithms NeurIPS 2021 Membership Inference Attacks on Deep Regression Models for Neuroimaging MIDL 2021 q-Paths: Generalizing the geometric annealing path using power means UAI 2021 All in the Exponential Family: Bregman Duality in Thermodynamic Variational Inference ICML 2020 Improving generalization by controlling label-noise information in neural network weights ICML 2020 Invariant Representations through Adversarial Forgetting AAAI 2020 Modeling Dialogues with Hashcode Representations: A Nonparametric Approach AAAI 2020 Auto-Encoding Total Correlation Explanation AISTATS 2019 Exact Rate-Distortion in Autoencoders via Echo Noise NeurIPS 2019 Fast structure learning with modular regularization NeurIPS 2019 Kernelized Hashcode Representations for Relation Extraction AAAI 2019 MixHop: Higher-Order Graph Convolutional Architectures via Sparsified Neighborhood Mixing ICML 2019 Nearly-Unsupervised Hashcode Representations for Biomedical Relation Extraction EMNLP 2019 Invariant Representations without Adversarial Training NeurIPS 2018 Sifting Common Information from Many Variables IJCAI 2017 Unsupervised Learning via Total Correlation Explanation IJCAI 2017 The Information Sieve ICML 2016 Variational Information Maximization for Feature Selection NeurIPS 2016 Efficient Estimation of Mutual Information for Strongly Dependent Variables AISTATS 2015 Maximally Informative Hierarchical Representations of High-Dimensional Data AISTATS 2015 Demystifying Information-Theoretic Clustering ICML 2014 Discovering Structure in High-Dimensional Data Through Correlation Explanation NeurIPS 2014 Statistical Tests for Contagion in Observational Social Network Studies AISTATS 2013