Greg Ver Steeg

190 papers A* 30A 15B 2C 1Misc 1Journal 109Unranked 31

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Discrete Stochastic Localization for Non-autoregressive Generation. CoRR Yunshu Wu, Jiayi Cheng, Partha Thakuria, Rob Brekelmans, Evangelos E. Papalexakis, Greg Ver Steeg
2026	J	`jnl`	Generation Order and Parallel Decoding in Masked Diffusion Models: An Information-Theoretic Perspective. CoRR Shaorong Zhang, Longxuan Yu, Rob Brekelmans, Luhan Tang, Salman Asif, Greg Ver Steeg
2026	J	`jnl`	Is Your Diffusion Sampler Actually Correct? A Sampler-Centric Evaluation of Discrete Diffusion Language Models. CoRR Luhan Tang, Longxuan Yu, Shaorong Zhang, Greg Ver Steeg
2026	J	`jnl`	Multi-modal Imputation for Alzheimer's Disease Classification. CoRR Abhijith Shaji, Tamoghna Chattopadhyay, Sophia I. Thomopoulos, Greg Ver Steeg, Paul M. Thompson, José Luis Ambite
2026	J	`jnl`	Spectral Regularization for Diffusion Models. CoRR Satish Chandran, Nícolas Roque dos Santos, Yunshu Wu, Greg Ver Steeg, Evangelos Papalexakis
2026	J	`jnl`	Thinking Out of Order: When Output Order Stops Reflecting Reasoning Order in Diffusion Language Models. CoRR Longxuan Yu, Yu Fu, Shaorong Zhang, Hui Liu, Mukund Varma T, Greg Ver Steeg, Yue Dong
2025	J	`jnl`	AbFlowNet: Optimizing Antibody-Antigen Binding Energy via Diffusion-GFlowNet Fusion. CoRR Abrar Rahman Abir, Haz Sameen Shahgir, Md Rownok Zahan Ratul, Md Toki Tahmid, Greg Ver Steeg, Yue Dong
2025	J	`jnl`	Denoising diffusion wavelet models for zero-shot medical image translation. Knowl. Based Syst. Yunxiang Li, Xianghao Kong, Jiacheng Xie, Greg Ver Steeg, You Zhang
2025	J	`jnl`	Diffusion Bridge Models for 3D Medical Image Translation. CoRR Shaorong Zhang, Tamoghna Chattopadhyay, Sophia I. Thomopoulos, José Luis Ambite, Paul M. Thompson, Greg Ver Steeg
2025	—	`conf`	FedDAPL: Toward Client-Private Generalization in Federated Learning. SIPAIM Soroosh Safari Loaliyan, José Luis Ambite, Paul M. Thompson, Neda Jahanshad, Greg Ver Steeg
2025	J	`jnl`	FedDAPL: Toward Client-Private Generalization in Federated Learning. CoRR Soroosh Safari Loaliyan, José Luis Ambite, Paul M. Thompson, Neda Jahanshad, Greg Ver Steeg
2025	—	`conf`	Generating diffusion MRI scalar maps from T1-weighted images using Reversible GANs. SIPAIM Tamoghna Chattopadhyay, Gautam Mehendale, Sophia I. Thomopoulos, Himanshu Joshi, Ganesan Venkatasubramanian, John P. John, José Luis Ambite, Greg Ver Steeg, Paul M. Thompson
2025	J	`jnl`	KG-LLM-Bench: A Scalable Benchmark for Evaluating LLM Reasoning on Textualized Knowledge Graphs. CoRR Elan Markowitz, Krupa Galiya, Greg Ver Steeg, Aram Galstyan
2025	Misc	`conf`	Knowledge Enhanced Multi-Domain Recommendations in an AI Assistant Application. ICASSP Elan Markowitz, Ziyan Jiang, Fan Yang, Xing Fan, Zheng Chen, Greg Ver Steeg, Aram Galstyan
2025	J	`jnl`	Local MAP Sampling for Diffusion Models. CoRR Shaorong Zhang, Rob Brekelmans, Greg Ver Steeg
2025	J	`jnl`	MMG: Mutual Information Estimation via the MMSE Gap in Diffusion. CoRR Longxuan Yu, Xing Shi, Xianghao Kong, Tong Jia, Greg Ver Steeg
2025	J	`jnl`	Making Sense Of Distributed Representations With Activation Spectroscopy. CoRR Kyle Reing, Greg Ver Steeg, Aram Galstyan
2025	J	`jnl`	Measurement-aligned Flow for Inverse Problem. CoRR Shaorong Zhang, Rob Brekelmans, Yunshu Wu, Greg Ver Steeg
2024	J	`jnl`	A federated learning architecture for secure and private neuroimaging analysis. Patterns Dimitris Stripelis, Umang Gupta, Hamza Saleem, Nikhil J. Dhinagar, Tanmay Ghai, Chrysovalantis Anastasiou, Rafael Sanchez, Greg Ver Steeg, Srivatsan Ravi, Muhammad Naveed, Paul M. Thompson, José Luis Ambite
2024	—	`conf`	Asymmetric Bias in Text-to-Image Generation with Adversarial Attacks. ACL (Findings) Haz Sameen Shahgir, Xianghao Kong, Greg Ver Steeg, Yue Dong
2024	A	`conf`	Biased User History Synthesis for Personalized Long-Tail Item Recommendation. RecSys Keshav Balasubramanian, Abdulla Alshabanah, Elan Markowitz, Greg Ver Steeg, Murali Annavaram
2024	—	`conf`	Comparative Analysis of Generalization and Harmonization Methods for 3D Brain fMRI Images: A Case Study on OpenBHB Dataset. CVPR Workshops Soroosh Safari Loaliyan, Greg Ver Steeg
2024	—	`conf`	Comparison of Explainable AI Models for MRI-Based Alzheimer's Disease Classification. SIPAIM Tamoghna Chattopadhyay, Neha Ann Joshy, Chirag Jagad, Emma J. Gleave, Sophia I. Thomopoulos, Yixue Feng, Julio E. Villalon-Reina, Emily Laltoo, Himanshu Joshi, Ganesan Venkatasubramanian, John P. John, Greg Ver Steeg, José Luis Ambite, Paul M. Thompson
2024	—	`conf`	Ensembled Prediction Intervals for Causal Outcomes Under Hidden Confounding. CLeaR Myrl G. Marmarelis, Greg Ver Steeg, Aram Galstyan, Fred Morstatter
2024	J	`jnl`	Exploring the Design Space of Diffusion Bridge Models via Stochasticity Control. CoRR Shaorong Zhang, Yuanbin Cheng, Xianghao Kong, Greg Ver Steeg
2024	J	`jnl`	Functional connectivity via total correlation: Analytical results in visual areas. Neurocomputing Qiang Li, Greg Ver Steeg, Jesus Malo
2024	A*	`conf`	Interpretable Diffusion via Information Decomposition. ICLR Xianghao Kong, Ollie Liu, Han Li, Dani Yogatama, Greg Ver Steeg
2024	A*	`conf`	Interpretable Measures of Conceptual Similarity by Complexity-Constrained Descriptive Auto-Encoding. CVPR Alessandro Achille, Greg Ver Steeg, Tian Yu Liu, Matthew Trager, Carson Klingenberg, Stefano Soatto
2024	J	`jnl`	Interpretable Measures of Conceptual Similarity by Complexity-Constrained Descriptive Auto-Encoding. CoRR Alessandro Achille, Greg Ver Steeg, Tian Yu Liu, Matthew Trager, Carson Klingenberg, Stefano Soatto
2024	J	`jnl`	Learning Morphisms with Gauss-Newton Approximation for Growing Networks. CoRR Neal Lawton, Aram Galstyan, Greg Ver Steeg
2024	A	`conf`	Policy Learning for Localized Interventions from Observational Data. AISTATS Myrl G. Marmarelis, Fred Morstatter, Aram Galstyan, Greg Ver Steeg
2024	—	`conf`	Prompt Perturbation Consistency Learning for Robust Language Models. EACL (Findings) Yao Qiang, Subhrangshu Nandi, Ninareh Mehrabi, Greg Ver Steeg, Anoop Kumar, Anna Rumshisky, Aram Galstyan
2024	J	`jnl`	Prompt Perturbation Consistency Learning for Robust Language Models. CoRR Yao Qiang, Subhrangshu Nandi, Ninareh Mehrabi, Greg Ver Steeg, Anoop Kumar, Anna Rumshisky, Aram Galstyan
2024	—	`conf`	QuAILoRA: Quantization-Aware Initialization for LoRA. ENLSP Neal Lawton, Aishwarya Padmakumar, Judith Gaspers, Jack FitzGerald, Anoop Kumar, Greg Ver Steeg, Aram Galstyan
2024	J	`jnl`	QuAILoRA: Quantization-Aware Initialization for LoRA. CoRR Neal Lawton, Aishwarya Padmakumar, Judith Gaspers, Jack FitzGerald, Anoop Kumar, Greg Ver Steeg, Aram Galstyan
2024	A*	`conf`	Your Diffusion Model is Secretly a Noise Classifier and Benefits from Contrastive Training. NeurIPS Yunshu Wu, Yingtao Luo, Xianghao Kong, Vagelis Papalexakis, Greg Ver Steeg
2024	J	`jnl`	Your Diffusion Model is Secretly a Noise Classifier and Benefits from Contrastive Training. CoRR Yunshu Wu, Yingtao Luo, Xianghao Kong, Evangelos E. Papalexakis, Greg Ver Steeg
2023	J	`jnl`	Asymmetric Bias in Text-to-Image Generation with Adversarial Attacks. CoRR Haz Sameen Shahgir, Xianghao Kong, Greg Ver Steeg, Yue Dong
2023	—	`conf`	Causal Sensitivity Analysis for Hidden Confounding: Modeling the Sex-Specific Role of Diet on the Aging Brain. MLCN@MICCAI Elizabeth Haddad, Myrl G. Marmarelis, Talia M. Nir, Aram Galstyan, Greg Ver Steeg, Neda Jahanshad
2023	J	`jnl`	Improving Mutual Information Estimation with Annealed and Energy-Based Bounds. CoRR Rob Brekelmans, Sicong Huang, Marzyeh Ghassemi, Greg Ver Steeg, Roger B. Grosse, Alireza Makhzani
2023	A*	`conf`	Information-Theoretic Diffusion. ICLR Xianghao Kong, Rob Brekelmans, Greg Ver Steeg
2023	J	`jnl`	Information-Theoretic Diffusion. CoRR Xianghao Kong, Rob Brekelmans, Greg Ver Steeg
2023	J	`jnl`	Interpretable Diffusion via Information Decomposition. CoRR Xianghao Kong, Ollie Liu, Han Li, Dani Yogatama, Greg Ver Steeg
2023	—	`conf`	Jointly Reparametrized Multi-Layer Adaptation for Efficient and Private Tuning. ACL (Findings) Umang Gupta, Aram Galstyan, Greg Ver Steeg
2023	J	`jnl`	Jointly Reparametrized Multi-Layer Adaptation for Efficient and Private Tuning. CoRR Umang Gupta, Aram Galstyan, Greg Ver Steeg
2023	—	`conf`	Measuring and Mitigating Local Instability in Deep Neural Networks. ACL (Findings) Arghya Datta, Subhrangshu Nandi, Jingcheng Xu, Greg Ver Steeg, He Xie, Anoop Kumar, Aram Galstyan
2023	J	`jnl`	Measuring and Mitigating Local Instability in Deep Neural Networks. CoRR Arghya Datta, Subhrangshu Nandi, Jingcheng Xu, Greg Ver Steeg, He Xie, Anoop Kumar, Aram Galstyan
2023	J	`jnl`	Multi-Task Knowledge Enhancement for Zero-Shot and Multi-Domain Recommendation in an AI Assistant Application. CoRR Elan Markowitz, Ziyan Jiang, Fan Yang, Xing Fan, Tony Chen, Greg Ver Steeg, Aram Galstyan
2023	—	`conf`	Neural Architecture Search for Parameter-Efficient Fine-tuning of Large Pre-trained Language Models. ACL (Findings) Neal Lawton, Anoop Kumar, Govind Thattai, Aram Galstyan, Greg Ver Steeg
2023	J	`jnl`	Neural Architecture Search for Parameter-Efficient Fine-tuning of Large Pre-trained Language Models. CoRR Neal Lawton, Anoop Kumar, Govind Thattai, Aram Galstyan, Greg Ver Steeg
2023	A	`conf`	Partial identification of dose responses with hidden confounders. UAI Myrl G. Marmarelis, Elizabeth Haddad, Andrew Jesson, Neda Jahanshad, Aram Galstyan, Greg Ver Steeg
2023	J	`jnl`	Tighter Prediction Intervals for Causal Outcomes Under Hidden Confounding. CoRR Myrl G. Marmarelis, Greg Ver Steeg, Aram Galstyan, Fred Morstatter
2023	—	`conf`	Transferring Models Trained on Natural Images to 3D MRI via Position Encoded Slice Models. ISBI Umang Gupta, Tamoghna Chattopadhyay, Nikhil J. Dhinagar, Paul M. Thompson, Greg Ver Steeg
2023	J	`jnl`	Transferring Models Trained on Natural Images to 3D MRI via Position Encoded Slice Models. CoRR Umang Gupta, Tamoghna Chattopadhyay, Nikhil J. Dhinagar, Paul M. Thompson, Greg Ver Steeg, Alzheimer's Disease Neuroimaging Initiative
2023	—	`conf`	Unsupervised harmonization of brain MRI using 3D CycleGANs and its effect on brain age prediction. SIPAIM Dheeraj Komandur, Umang Gupta, Tamoghna Chattopadhyay, Nikhil J. Dhinagar, Sophia I. Thomopoulos, Jiu-Chiuan Chen, Dan Beavers, Greg Ver Steeg, Paul M. Thompson
2022	J	`jnl`	A Metric Space for Point Process Excitations. J. Artif. Intell. Res. Myrl G. Marmarelis, Greg Ver Steeg, Aram Galstyan
2022	J	`jnl`	Bounding the Effects of Continuous Treatments for Hidden Confounders. CoRR Myrl G. Marmarelis, Greg Ver Steeg, Aram Galstyan
2022	A*	`conf`	Failure Modes of Domain Generalization Algorithms. CVPR Tigran Galstyan, Hrayr Harutyunyan, Hrant Khachatrian, Greg Ver Steeg, Aram Galstyan
2022	J	`jnl`	Federated Progressive Sparsification (Purge, Merge, Tune)+. CoRR Dimitris Stripelis, Umang Gupta, Greg Ver Steeg, José Luis Ambite
2022	B	`conf`	Formal limitations of sample-wise information-theoretic generalization bounds. ITW Hrayr Harutyunyan, Greg Ver Steeg, Aram Galstyan
2022	J	`jnl`	Formal limitations of sample-wise information-theoretic generalization bounds. CoRR Hrayr Harutyunyan, Greg Ver Steeg, Aram Galstyan
2022	J	`jnl`	Functional Connectome of the Human Brain with Total Correlation. Entropy Qiang Li, Greg Ver Steeg, Shujian Yu, Jesus Malo
2022	A*	`conf`	Improving Mutual Information Estimation with Annealed and Energy-Based Bounds. ICLR Rob Brekelmans, Sicong Huang, Marzyeh Ghassemi, Greg Ver Steeg, Roger Baker Grosse, Alireza Makhzani
2022	J	`jnl`	Inferring topological transitions in pattern-forming processes with self-supervised learning. CoRR Marcin Abram, Keith Burghardt, Greg Ver Steeg, Aram Galstyan, Rémi Dingreville
2022	—	`conf`	Mitigating Gender Bias in Distilled Language Models via Counterfactual Role Reversal. ACL (Findings) Umang Gupta, Jwala Dhamala, Varun Kumar, Apurv Verma, Yada Pruksachatkun, Satyapriya Krishna, Rahul Gupta, Kai-Wei Chang, Greg Ver Steeg, Aram Galstyan
2022	J	`jnl`	Mitigating Gender Bias in Distilled Language Models via Counterfactual Role Reversal. CoRR Umang Gupta, Jwala Dhamala, Varun Kumar, Apurv Verma, Yada Pruksachatkun, Satyapriya Krishna, Rahul Gupta, Kai-Wei Chang, Greg Ver Steeg, Aram Galstyan
2022	J	`jnl`	Secure Federated Learning for Neuroimaging. CoRR Dimitris Stripelis, Umang Gupta, Hamza Saleem, Nikhil J. Dhinagar, Tanmay Ghai, Rafael Sanchez, Chrysovalantis Anastasiou, Armaghan Asghar, Greg Ver Steeg, Srivatsan Ravi, Muhammad Naveed, Paul M. Thompson, José Luis Ambite
2022	—	`conf`	StATIK: Structure and Text for Inductive Knowledge Graph Completion. NAACL-HLT (Findings) Elan Markowitz, Keshav Balasubramanian, Mehrnoosh Mirtaheri, Murali Annavaram, Aram Galstyan, Greg Ver Steeg
2022	—	`conf`	Temporal Generalization for Spoken Language Understanding. NAACL-HLT (Industry Papers) Judith Gaspers, Anoop Kumar, Greg Ver Steeg, Aram Galstyan
2022	—	`conf`	Towards Sparsified Federated Neuroimaging Models via Weight Pruning. DeCaF/FAIR@MICCAI Dimitris Stripelis, Umang Gupta, Nikhil J. Dhinagar, Greg Ver Steeg, Paul M. Thompson, José Luis Ambite
2022	J	`jnl`	Towards Sparsified Federated Neuroimaging Models via Weight Pruning. CoRR Dimitris Stripelis, Umang Gupta, Nikhil J. Dhinagar, Greg Ver Steeg, Paul M. Thompson, José Luis Ambite
2021	J	`jnl`	Attributing Fair Decisions with Attention Interventions. CoRR Ninareh Mehrabi, Umang Gupta, Fred Morstatter, Greg Ver Steeg, Aram Galstyan
2021	A*	`conf`	Controllable Guarantees for Fair Outcomes via Contrastive Information Estimation. AAAI Umang Gupta, Aaron M. Ferber, Bistra Dilkina, Greg Ver Steeg
2021	J	`jnl`	Controllable Guarantees for Fair Outcomes via Contrastive Information Estimation. CoRR Umang Gupta, Aaron M. Ferber, Bistra Dilkina, Greg Ver Steeg
2021	J	`jnl`	Discovering Higher-Order Interactions Through Neural Information Decomposition. Entropy Kyle Reing, Greg Ver Steeg, Aram Galstyan
2021	J	`jnl`	Failure Modes of Domain Generalization Algorithms. CoRR Tigran Galstyan, Hrayr Harutyunyan, Hrant Khachatrian, Greg Ver Steeg, Aram Galstyan
2021	J	`jnl`	Fast Graph Learning with Unique Optimal Solutions. CoRR Sami Abu-El-Haija, Valentino Crespi, Greg Ver Steeg, Aram Galstyan
2021	A*	`conf`	Graph Traversal with Tensor Functionals: A Meta-Algorithm for Scalable Learning. ICLR Elan Sopher Markowitz, Keshav Balasubramanian, Mehrnoosh Mirtaheri, Sami Abu-El-Haija, Bryan Perozzi, Greg Ver Steeg, Aram Galstyan
2021	J	`jnl`	Graph Traversal with Tensor Functionals: A Meta-Algorithm for Scalable Learning. CoRR Elan Markowitz, Keshav Balasubramanian, Mehrnoosh Mirtaheri, Sami Abu-El-Haija, Bryan Perozzi, Greg Ver Steeg, Aram Galstyan
2021	A*	`conf`	Hamiltonian Dynamics with Non-Newtonian Momentum for Rapid Sampling. NeurIPS Greg Ver Steeg, Aram Galstyan
2021	J	`jnl`	Hamiltonian Dynamics with Non-Newtonian Momentum for Rapid Sampling. CoRR Greg Ver Steeg, Aram Galstyan
2021	J	`jnl`	Identifying and Analyzing Cryptocurrency Manipulations in Social Media. IEEE Trans. Comput. Soc. Syst. Mehrnoosh Mirtaheri, Sami Abu-El-Haija, Fred Morstatter, Greg Ver Steeg, Aram Galstyan
2021	A*	`conf`	Implicit SVD for Graph Representation Learning. NeurIPS Sami Abu-El-Haija, Hesham Mostafa, Marcel Nassar, Valentino Crespi, Greg Ver Steeg, Aram Galstyan
2021	J	`jnl`	Implicit SVD for Graph Representation Learning. CoRR Sami Abu-El-Haija, Hesham Mostafa, Marcel Nassar, Valentino Crespi, Greg Ver Steeg, Aram Galstyan
2021	—	`conf`	Improved Brain Age Estimation With Slice-Based Set Networks. ISBI Umang Gupta, Pradeep K. Lam, Greg Ver Steeg, Paul M. Thompson
2021	J	`jnl`	Improved Brain Age Estimation with Slice-based Set Networks. CoRR Umang Gupta, Pradeep Lam, Greg Ver Steeg, Paul Thompson
2021	A	`conf`	Influence Decompositions For Neural Network Attribution. AISTATS Kyle Reing, Greg Ver Steeg, Aram Galstyan
2021	A*	`conf`	Information-theoretic generalization bounds for black-box learning algorithms. NeurIPS Hrayr Harutyunyan, Maxim Raginsky, Greg Ver Steeg, Aram Galstyan
2021	J	`jnl`	Information-theoretic generalization bounds for black-box learning algorithms. CoRR Hrayr Harutyunyan, Maxim Raginsky, Greg Ver Steeg, Aram Galstyan
2021	C	`conf`	Layer-Wise Neural Network Compression via Layer Fusion. ACML James O'Neill, Greg Ver Steeg, Aram Galstyan
2021	—	`conf`	Membership Inference Attacks on Deep Regression Models for Neuroimaging. MIDL Umang Gupta, Dimitris Stripelis, Pradeep K. Lam, Paul M. Thompson, José Luis Ambite, Greg Ver Steeg
2021	J	`jnl`	Membership Inference Attacks on Deep Regression Models for Neuroimaging. CoRR Umang Gupta, Dimitris Stripelis, Pradeep K. Lam, Paul M. Thompson, José Luis Ambite, Greg Ver Steeg
2021	J	`jnl`	Secure Neuroimaging Analysis using Federated Learning with Homomorphic Encryption. CoRR Dimitris Stripelis, Hamza Saleem, Tanmay Ghai, Nikhil J. Dhinagar, Umang Gupta, Chrysovalantis Anastasiou, Greg Ver Steeg, Srivatsan Ravi, Muhammad Naveed, Paul M. Thompson, José Luis Ambite
2021	J	`jnl`	q-Paths: Generalizing the Geometric Annealing Path using Power Means. CoRR Vaden Masrani, Rob Brekelmans, Thang Bui, Frank Nielsen, Aram Galstyan, Greg Ver Steeg, Frank Wood
2021	A	`conf`	q-Paths: Generalizing the geometric annealing path using power means. UAI Vaden Masrani, Rob Brekelmans, Thang Bui, Frank Nielsen, Aram Galstyan, Greg Ver Steeg, Frank Wood
2020	A*	`conf`	All in the Exponential Family: Bregman Duality in Thermodynamic Variational Inference. ICML Rob Brekelmans, Vaden Masrani, Frank Wood, Greg Ver Steeg, Aram Galstyan
2020	J	`jnl`	All in the Exponential Family: Bregman Duality in Thermodynamic Variational Inference. CoRR Rob Brekelmans, Vaden Masrani, Frank Wood, Greg Ver Steeg, Aram Galstyan
2020	J	`jnl`	Annealed Importance Sampling with q-Paths. CoRR Rob Brekelmans, Vaden Masrani, Thang Bui, Frank Wood, Aram Galstyan, Greg Ver Steeg, Frank Nielsen
2020	J	`jnl`	Compressing Deep Neural Networks via Layer Fusion. CoRR James O'Neill, Greg Ver Steeg, Aram Galstyan
2020	J	`jnl`	Event Cartography: Latent Point Process Embeddings. CoRR Myrl G. Marmarelis, Greg Ver Steeg, Aram Galstyan
2020	J	`jnl`	Improving Generalization by Controlling Label-Noise Information in Neural Network Weights. CoRR Hrayr Harutyunyan, Kyle Reing, Greg Ver Steeg, Aram Galstyan
2020	A*	`conf`	Improving generalization by controlling label-noise information in neural network weights. ICML Hrayr Harutyunyan, Kyle Reing, Greg Ver Steeg, Aram Galstyan
2020	A*	`conf`	Invariant Representations through Adversarial Forgetting. AAAI Ayush Jaiswal, Daniel Moyer, Greg Ver Steeg, Wael AbdAlmageed, Premkumar Natarajan
2020	J	`jnl`	Likelihood Ratio Exponential Families. CoRR Rob Brekelmans, Frank Nielsen, Alireza Makhzani, Aram Galstyan, Greg Ver Steeg
2020	J	`jnl`	Maximizing Multivariate Information With Error-Correcting Codes. IEEE Trans. Inf. Theory Kyle Reing, Greg Ver Steeg, Aram Galstyan
2020	A*	`conf`	Modeling Dialogues with Hashcode Representations: A Nonparametric Approach. AAAI Sahil Garg, Irina Rish, Guillermo A. Cecchi, Palash Goyal, Sarik Ghazarian, Shuyang Gao, Greg Ver Steeg, Aram Galstyan
2020	J	`jnl`	Overview of Scanner Invariant Representations. CoRR Daniel Moyer, Greg Ver Steeg, Paul M. Thompson
2020	J	`jnl`	Robust Classification under Class-Dependent Domain Shift. CoRR Tigran Galstyan, Hrant Khachatrian, Greg Ver Steeg, Aram Galstyan
2019	A	`conf`	Auto-Encoding Total Correlation Explanation. AISTATS Shuyang Gao, Rob Brekelmans, Greg Ver Steeg, Aram Galstyan
2019	J	`jnl`	Discovery and Separation of Features for Invariant Representation Learning. CoRR Ayush Jaiswal, Rob Brekelmans, Daniel Moyer, Greg Ver Steeg, Wael AbdAlmageed, Premkumar Natarajan
2019	J	`jnl`	Efficient Covariance Estimation from Temporal Data. CoRR Hrayr Harutyunyan, Daniel Moyer, Hrant Khachatrian, Greg Ver Steeg, Aram Galstyan
2019	A*	`conf`	Exact Rate-Distortion in Autoencoders via Echo Noise. NeurIPS Rob Brekelmans, Daniel Moyer, Aram Galstyan, Greg Ver Steeg
2019	J	`jnl`	Exact Rate-Distortion in Autoencoders via Echo Noise. CoRR Rob Brekelmans, Daniel Moyer, Aram Galstyan, Greg Ver Steeg
2019	A*	`conf`	Fast structure learning with modular regularization. NeurIPS Greg Ver Steeg, Hrayr Harutyunyan, Daniel Moyer, Aram Galstyan
2019	J	`jnl`	Identifying and Analyzing Cryptocurrency Manipulations in Social Media. CoRR Mehrnoosh Mirtaheri, Sami Abu-El-Haija, Fred Morstatter, Greg Ver Steeg, Aram Galstyan
2019	J	`jnl`	Invariant Representations through Adversarial Forgetting. CoRR Ayush Jaiswal, Daniel Moyer, Greg Ver Steeg, Wael AbdAlmageed, Premkumar Natarajan
2019	A*	`conf`	Kernelized Hashcode Representations for Relation Extraction. AAAI Sahil Garg, Aram Galstyan, Greg Ver Steeg, Irina Rish, Guillermo A. Cecchi, Shuyang Gao
2019	A*	`conf`	MixHop: Higher-Order Graph Convolutional Architectures via Sparsified Neighborhood Mixing. ICML Sami Abu-El-Haija, Bryan Perozzi, Amol Kapoor, Nazanin Alipourfard, Kristina Lerman, Hrayr Harutyunyan, Greg Ver Steeg, Aram Galstyan
2019	J	`jnl`	MixHop: Higher-Order Graph Convolutional Architectures via Sparsified Neighborhood Mixing. CoRR Sami Abu-El-Haija, Bryan Perozzi, Amol Kapoor, Hrayr Harutyunyan, Nazanin Alipourfard, Kristina Lerman, Greg Ver Steeg, Aram Galstyan
2019	—	`conf`	Nearly-Unsupervised Hashcode Representations for Biomedical Relation Extraction. EMNLP/IJCNLP (1) Sahil Garg, Aram Galstyan, Greg Ver Steeg, Guillermo A. Cecchi
2019	J	`jnl`	Nearly-Unsupervised Hashcode Representations for Relation Extraction. CoRR Sahil Garg, Aram Galstyan, Greg Ver Steeg, Guillermo A. Cecchi
2019	J	`jnl`	Scanner Invariant Representations for Diffusion MRI Harmonization. CoRR Daniel Moyer, Greg Ver Steeg, Chantal M. W. Tax, Paul M. Thompson
2018	A	`conf`	A Forest Mixture Bound for Block-Free Parallel Inference. UAI Neal Lawton, Greg Ver Steeg, Aram Galstyan
2018	J	`jnl`	A Forest Mixture Bound for Block-Free Parallel Inference. CoRR Neal Lawton, Aram Galstyan, Greg Ver Steeg
2018	J	`jnl`	Auto-Encoding Total Correlation Explanation. CoRR Shuyang Gao, Rob Brekelmans, Greg Ver Steeg, Aram Galstyan
2018	—	`conf`	Dialogue Modeling Via Hash Functions. LaCATODA@IJCAI Sahil Garg, Guillermo A. Cecchi, Irina Rish, Shuyang Gao, Greg Ver Steeg, Sarik Ghazarian, Palash Goyal, Aram Galstyan
2018	J	`jnl`	Evading the Adversary in Invariant Representation. CoRR Daniel Moyer, Shuyang Gao, Rob Brekelmans, Greg Ver Steeg, Aram Galstyan
2018	A*	`conf`	Invariant Representations without Adversarial Training. NeurIPS Daniel Moyer, Shuyang Gao, Rob Brekelmans, Aram Galstyan, Greg Ver Steeg
2018	J	`jnl`	Maximizing Multivariate Information with Error-Correcting Codes. CoRR Kyle Reing, Greg Ver Steeg, Aram Galstyan
2018	J	`jnl`	Measures of Tractography Convergence. CoRR Daniel Moyer, Paul M. Thompson, Greg Ver Steeg
2018	J	`jnl`	Stochastic Learning of Nonstationary Kernels for Natural Language Modeling. CoRR Sahil Garg, Greg Ver Steeg, Aram Galstyan
2017	J	`jnl`	Anchored Correlation Explanation: Topic Modeling with Minimal Domain Knowledge. Trans. Assoc. Comput. Linguistics Ryan J. Gallagher, Kyle Reing, David C. Kale, Greg Ver Steeg
2017	J	`jnl`	Disentangled Representations via Synergy Minimization. CoRR Greg Ver Steeg, Rob Brekelmans, Hrayr Harutyunyan, Aram Galstyan
2017	—	`conf`	Disentangled representations via synergy minimization. Allerton Greg Ver Steeg, Rob Brekelmans, Hrayr Harutyunyan, Aram Galstyan
2017	J	`jnl`	Low Complexity Gaussian Latent Factor Models and a Blessing of Dimensionality. CoRR Greg Ver Steeg, Aram Galstyan
2017	J	`jnl`	Memory-induced mechanism for self-sustaining activity in networks. CoRR Armen E. Allahverdyan, Greg Ver Steeg, Aram Galstyan
2017	A*	`conf`	Scalable Temporal Latent Space Inference for Link Prediction in Dynamic Social Networks (Extended Abstract). ICDE Linhong Zhu, Dong Guo, Junming Yin, Greg Ver Steeg, Aram Galstyan
2017	A*	`conf`	Sifting Common Information from Many Variables. IJCAI Greg Ver Steeg, Shuyang Gao, Kyle Reing, Aram Galstyan
2017	A*	`conf`	The Spread of Physical Activity Through Social Networks. WWW David Stück, Haraldur Tómas Hallgrímsson, Greg Ver Steeg, Alessandro Epasto, Luca Foschini
2017	J	`jnl`	Unifying Local and Global Change Detection in Dynamic Networks. CoRR Wenzhe Li, Dong Guo, Greg Ver Steeg, Aram Galstyan
2017	A*	`conf`	Unsupervised Learning via Total Correlation Explanation. IJCAI Greg Ver Steeg
2016	J	`jnl`	Anchored Correlation Explanation: Topic Modeling with Minimal Domain Knowledge. CoRR Ryan J. Gallagher, Kyle Reing, David C. Kale, Greg Ver Steeg
2016	A*	`conf`	Latent Space Model for Multi-Modal Social Data. WWW Yoon-Sik Cho, Greg Ver Steeg, Emilio Ferrara, Aram Galstyan
2016	B	`conf`	Relative value of diverse brain MRI and blood-based biomarkers for predicting cognitive decline in the elderly. Image Processing Sarah K. Madsen, Greg Ver Steeg, Madelaine Daianu, Adam Mezher, Neda Jahanshad, Talia M. Nir, Xue Hua, Boris A. Gutman, Aram Galstyan, Paul M. Thompson
2016	J	`jnl`	Scalable Temporal Latent Space Inference for Link Prediction in Dynamic Social Networks. IEEE Trans. Knowl. Data Eng. Linhong Zhu, Dong Guo, Junming Yin, Greg Ver Steeg, Aram Galstyan
2016	J	`jnl`	Sifting Common Information from Many Variables. CoRR Greg Ver Steeg, Shuyang Gao, Kyle Reing, Aram Galstyan
2016	A*	`conf`	The Information Sieve. ICML Greg Ver Steeg, Aram Galstyan
2016	J	`jnl`	Toward Interpretable Topic Discovery via Anchored Correlation Explanation. CoRR Kyle Reing, David C. Kale, Greg Ver Steeg, Aram Galstyan
2016	—	`conf`	Variational Information Maximization for Feature Selection. NIPS Shuyang Gao, Greg Ver Steeg, Aram Galstyan
2016	J	`jnl`	Variational Information Maximization for Feature Selection. CoRR Shuyang Gao, Greg Ver Steeg, Aram Galstyan
2015	—	`conf`	Disentangling the Lexicons of Disaster Response in Twitter. WWW (Companion Volume) Nathan O. Hodas, Greg Ver Steeg, Joshua J. Harrison, Satish Chikkagoudar, Eric Bell, Courtney D. Corley
2015	A	`conf`	Efficient Estimation of Mutual Information for Strongly Dependent Variables. AISTATS Shuyang Gao, Greg Ver Steeg, Aram Galstyan
2015	A	`conf`	Estimating Mutual Information by Local Gaussian Approximation. UAI Shuyang Gao, Greg Ver Steeg, Aram Galstyan
2015	J	`jnl`	Estimating Mutual Information by Local Gaussian Approximation. CoRR Shuyang Gao, Greg Ver Steeg, Aram Galstyan
2015	—	`conf`	Information-Theoretic Clustering of Neuroimaging Metrics Related to Cognitive Decline in the Elderly. MCV@MICCAI Madelaine Daianu, Greg Ver Steeg, Adam Mezher, Neda Jahanshad, Talia M. Nir, Xiaoran Yan, Gautam Prasad, Kristina Lerman, Aram Galstyan, Paul M. Thompson
2015	—	`conf`	Information-theoretic characterization of blood panel predictors for brain atrophy and cognitive decline in the elderly. ISBI Sarah K. Madsen, Greg Ver Steeg, Adam Mezher, Neda Jahanshad, Talia M. Nir, Xue Hua, Boris A. Gutman, Aram Galstyan, Paul M. Thompson
2015	J	`jnl`	Latent Space Model for Multi-Modal Social Data. CoRR Yoon-Sik Cho, Greg Ver Steeg, Emilio Ferrara, Aram Galstyan
2015	A	`conf`	Maximally Informative Hierarchical Representations of High-Dimensional Data. AISTATS Greg Ver Steeg, Aram Galstyan
2015	J	`jnl`	The Information Sieve. CoRR Greg Ver Steeg, Aram Galstyan
2014	A*	`conf`	Demystifying Information-Theoretic Clustering. ICML Greg Ver Steeg, Aram Galstyan, Fei Sha, Simon DeDeo
2014	—	`conf`	Discovering Structure in High-Dimensional Data Through Correlation Explanation. NIPS Greg Ver Steeg, Aram Galstyan
2014	J	`jnl`	Discovering Structure in High-Dimensional Data Through Correlation Explanation. CoRR Greg Ver Steeg, Aram Galstyan
2014	J	`jnl`	Efficient Estimation of Mutual Information for Strongly Dependent Variables. CoRR Shuyang Gao, Greg Ver Steeg, Aram Galstyan
2014	J	`jnl`	Maximally Informative Hierarchical Representations of High-Dimensional Data. CoRR Greg Ver Steeg, Aram Galstyan
2014	—	`ch.`	Mixed Membership Blockmodels for Dynamic Networks with Feedback. Handbook of Mixed Membership Models and Their Applications Yoon-Sik Cho, Greg Ver Steeg, Aram Galstyan
2014	J	`jnl`	Modeling Temporal Activity Patterns in Dynamic Social Networks. IEEE Trans. Comput. Soc. Syst. Vasanthan Raghavan, Greg Ver Steeg, Aram Galstyan, Alexander G. Tartakovsky
2014	J	`jnl`	Scalable Link Prediction in Dynamic Networks via Non-Negative Matrix Factorization. CoRR Linhong Zhu, Greg Ver Steeg, Aram Galstyan
2014	J	`jnl`	Understanding confounding effects in linguistic coordination: an information-theoretic approach. CoRR Shuyang Gao, Greg Ver Steeg, Aram Galstyan
2014	A*	`conf`	Where and Why Users "Check In". AAAI Yoon-Sik Cho, Greg Ver Steeg, Aram Galstyan
2013	—	`conf`	Coupled hidden markov models for user activity in social networks. ICME Workshops Vasanthan Raghavan, Greg Ver Steeg, Aram Galstyan, Alexander G. Tartakovsky
2013	J	`jnl`	Demystifying Information-Theoretic Clustering. CoRR Greg Ver Steeg, Aram Galstyan, Fei Sha, Simon DeDeo
2013	A	`conf`	Information-theoretic measures of influence based on content dynamics. WSDM Greg Ver Steeg, Aram Galstyan
2013	J	`jnl`	Modeling Temporal Activity Patterns in Dynamic Social Networks CoRR Vasanthan Raghavan, Greg Ver Steeg, Aram Galstyan, Alexander G. Tartakovsky
2013	J	`jnl`	Phase Transitions in Community Detection: A Solvable Toy Model. CoRR Greg Ver Steeg, Cristopher Moore, Aram Galstyan, Armen E. Allahverdyan
2013	A	`conf`	Statistical Tests for Contagion in Observational Social Network Studies. AISTATS Greg Ver Steeg, Aram Galstyan
2012	J	`jnl`	Inferring Predictive Links in Social Media Using Content Transfer CoRR Greg Ver Steeg, Aram Galstyan
2012	—	`conf`	Information Theoretic Tools for Social Media. #MSM Greg Ver Steeg
2012	A*	`conf`	Information transfer in social media. WWW Greg Ver Steeg, Aram Galstyan
2012	J	`jnl`	Statistical Tests for Contagion in Observational Social Network Studies CoRR Greg Ver Steeg, Aram Galstyan
2011	A	`conf`	A Sequence of Relaxation Constraining Hidden Variable Models. UAI Greg Ver Steeg, Aram Galstyan
2011	J	`jnl`	A Sequence of Relaxations Constraining Hidden Variable Models CoRR Greg Ver Steeg, Aram Galstyan
2011	A*	`conf`	Co-Evolution of Selection and Influence in Social Networks. AAAI Yoon-Sik Cho, Greg Ver Steeg, Aram Galstyan
2011	J	`jnl`	Co-evolution of Selection and Influence in Social Networks CoRR Yoon-Sik Cho, Greg Ver Steeg, Aram Galstyan
2011	J	`jnl`	Information Transfer in Social Media CoRR Greg Ver Steeg, Aram Galstyan
2011	—	`conf`	Social Mechanics: An Empirically Grounded Science of Social Media. The Future of the Social Web Kristina Lerman, Aram Galstyan, Greg Ver Steeg, Tad Hogg
2011	J	`jnl`	Statistical Mechanics of Semi-Supervised Clustering in Sparse Graphs CoRR Aram Galstyan, Greg Ver Steeg, Armen E. Allahverdyan
2011	A	`conf`	Statistical Mechanics of Semi-Supervised Clustering in Sparse Graphs (Abstract). UAI Greg Ver Steeg, Aram Galstyan, Armen E. Allahverdyan
2011	A	`conf`	What Stops Social Epidemics? ICWSM Greg Ver Steeg, Rumi Ghosh, Kristina Lerman
2011	J	`jnl`	What stops social epidemics? CoRR Greg Ver Steeg, Rumi Ghosh, Kristina Lerman
2009	J	`jnl`	Relaxed uncertainty relations and information processing. Quantum Inf. Comput. Greg Ver Steeg, Stephanie Wehner