MAP Inference in Chains using Column Generation. - David Belanger 002; Alexandre Passos; Sebastian Riedel 001; Andrew McCallum (NIPS, 2012)

Universal Schema for Slot Filling and Cold Start: UMass IESL at TACKBP 2013. - Sameer Singh 001; Limin Yao; David Belanger 002; Ari Kobren; Sam Anzaroot; Mike Wick; Alexandre Passos; Harshal Pandya; Jinho D. Choi; Brian Martin; Andrew McCallum (TAC, 2013)

Learning Soft Linear Constraints with Application to Citation Field Extraction. - Sam Anzaroot; Alexandre Passos; David Belanger 002; Andrew McCallum (ACL (1), 2014)

Message Passing for Soft Constraint Dual Decomposition. - David Belanger 002; Alexandre Passos; Sebastian Riedel 001; Andrew McCallum (UAI, 2014)

A Linear Dynamical System Model for Text. - David Belanger 002; Sham M. Kakade (ICML, 2015)

Building Knowledge Bases with Universal Schema: Cold Start and Slot-Filling Approaches. - Benjamin Roth 001; Nicholas Monath; David Belanger 002; Emma Strubell; Patrick Verga; Andrew McCallum (TAC, 2015)

Bethe Projections for Non-Local Inference. - Luke Vilnis; David Belanger 002; Daniel Sheldon; Andrew McCallum (UAI, 2015)

Bethe Learning of Conditional Random Fields via MAP Decoding. - Kui Tang; Nicholas Ruozzi; David Belanger 002; Tony Jebara (CoRR, 2015)

Bethe Learning of Graphical Models via MAP Decoding. - Kui Tang; Nicholas Ruozzi; David Belanger 002; Tony Jebara (AISTATS, 2016)

Incorporating Selectional Preferences in Multi-hop Relation Extraction. - Rajarshi Das; Arvind Neelakantan; David Belanger 002; Andrew McCallum (AKBC@NAACL-HLT, 2016)

Structured Prediction Energy Networks. - David Belanger 002; Andrew McCallum (ICML, 2016)

Multilingual Relation Extraction using Compositional Universal Schema. - Patrick Verga; David Belanger 002; Emma Strubell; Benjamin Roth 001; Andrew McCallum (HLT-NAACL, 2016)

Ask the GRU: Multi-task Learning for Deep Text Recommendations. - Trapit Bansal; David Belanger 002; Andrew McCallum (RecSys, 2016)

Ask the GRU: Multi-Task Learning for Deep Text Recommendations. - Trapit Bansal; David Belanger 002; Andrew McCallum (CoRR, 2016)

Synthesizing Normalized Faces from Facial Identity Features. - Forrester Cole; David Belanger 002; Dilip Krishnan; Aaron Sarna; Inbar Mosseri; William T. Freeman (CVPR, 2017)

Chains of Reasoning over Entities, Relations, and Text using Recurrent Neural Networks. - Rajarshi Das; Arvind Neelakantan; David Belanger 002; Andrew McCallum (EACL (1), 2017)

Fast and Accurate Entity Recognition with Iterated Dilated Convolutions. - Emma Strubell; Patrick Verga; David Belanger 002; Andrew McCallum (EMNLP, 2017)

End-to-End Learning for Structured Prediction Energy Networks. - David Belanger 002; Bishan Yang; Andrew McCallum (ICML, 2017)

Face Synthesis from Facial Identity Features. - Forrester Cole; David Belanger 002; Dilip Krishnan; Aaron Sarna; Inbar Mosseri; William T. Freeman (CoRR, 2017)

Fast and Accurate Sequence Labeling with Iterated Dilated Convolutions. - Emma Strubell; Patrick Verga; David Belanger 002; Andrew McCallum (CoRR, 2017)

Low-Rank Hidden State Embeddings for Viterbi Sequence Labeling. - Dung Thai; Shikhar Murty; Trapit Bansal; Luke Vilnis; David Belanger 002; Andrew McCallum (CoRR, 2017)

Learning Latent Permutations with Gumbel-Sinkhorn Networks. - Gonzalo E. Mena; David Belanger 002; Scott W. Linderman; Jasper Snoek (ICLR (Poster), 2018)

Boundless: Generative Adversarial Networks for Image Extension. - Dilip Krishnan; Piotr Teterwak; Aaron Sarna; Aaron Maschinot; Ce Liu 001; David Belanger 002; William T. Freeman (ICCV, 2019)

Model-based reinforcement learning for biological sequence design. - Christof Angermüller; David Dohan; David Belanger 002; Ramya Deshpande; Kevin Murphy 002; Lucy J. Colwell (ICLR, 2020)

Population-Based Black-Box Optimization for Biological Sequence Design. - Christof Angermüller; David Belanger 002; Andreea Gane; Zelda Mariet; David Dohan; Kevin Murphy 002; Lucy J. Colwell; D. Sculley (ICML, 2020)

Masked Language Modeling for Proteins via Linearly Scalable Long-Context Transformers. - Krzysztof Choromanski; Valerii Likhosherstov; David Dohan; Xingyou Song; Jared Davis; Tamás Sarlós; David Belanger 002; Lucy J. Colwell; Adrian Weller (CoRR, 2020)

Fixed-Length Protein Embeddings using Contextual Lenses. - Amir Shanehsazzadeh; David Belanger 002; David Dohan (CoRR, 2020)

Is Transfer Learning Necessary for Protein Landscape Prediction? - Amir Shanehsazzadeh; David Belanger 002; David Dohan (CoRR, 2020)

Critiquing Protein Family Classification Models Using Sufficient Input Subsets. - Brandon Carter 001; Maxwell L. Bileschi; Jamie Smith; Theo Sanderson; Drew Bryant; David Belanger 002; Lucy J. Colwell (J. Comput. Biol., 2020)

Generalizing Few-Shot Classification of Whole-Genome Doubling Across Cancer Types. - Sherry Chao; David Belanger 002 (ICCVW, 2021)

Rethinking Attention with Performers. - Krzysztof Marcin Choromanski; Valerii Likhosherstov; David Dohan; Xingyou Song; Andreea Gane; Tamás Sarlós; Peter Hawkins; Jared Quincy Davis; Afroz Mohiuddin; Lukasz Kaiser; David Benjamin Belanger; Lucy J. Colwell; et al. (ICLR, 2021)

Improving Protein Function Annotation via Unsupervised Pre-training: Robustness, Efficiency, and Insights. - David Dohan; Andreea Gane; Maxwell L. Bileschi; David Belanger 002; Lucy J. Colwell (KDD, 2021)

Constrained Discrete Black-Box Optimization using Mixed-Integer Programming. - Theodore P. Papalexopoulos; Christian Tjandraatmadja; Ross Anderson; Juan Pablo Vielma; David Belanger 002 (ICML, 2022)