Mike Wu - RankMe

61 papers A* 13A 2B 4Journal 33Unranked 8

Year	Rank	Type	Title / Venue / Authors
2022	J	`jnl`	Constant Power Root Market Makers. CoRR Mike Wu, Will McTighe
2022	—	`—`	Extensions and applications of deep probabilistic inference for generative models. Mike Wu
2022	A*	`conf`	Foundation Posteriors for Approximate Probabilistic Inference. NeurIPS Mike Wu, Noah D. Goodman
2022	J	`jnl`	Foundation Posteriors for Approximate Probabilistic Inference. CoRR Mike Wu, Noah D. Goodman
2022	J	`jnl`	Know Thy Student: Interactive Learning with Gaussian Processes. CoRR Rose E. Wang, Mike Wu, Noah D. Goodman
2022	J	`jnl`	Tutela: An Open-Source Tool for Assessing User-Privacy on Ethereum and Tornado Cash. CoRR Mike Wu, Will McTighe, Kaili Wang, István András Seres, Nick Bax, Manuel Puebla, Mariano Mendez, Federico Carrone, Tomás De Mattey, Herman O. Demaestri, Mariano Nicolini, Pedro Fontana
2021	A*	`conf`	Conditional Negative Sampling for Contrastive Learning of Visual Representations. ICLR Mike Wu, Milan Mossé, Chengxu Zhuang, Daniel Yamins, Noah D. Goodman
2021	B	`conf`	Generative Grading: Near Human-level Accuracy for Automated Feedback on Richly Structured Problems. EDM Ali Malik, Mike Wu, Vrinda Vasavada, Jinpeng Song, Madison Coots, John Mitchell, Noah D. Goodman, Chris Piech
2021	A*	`conf`	Improving Compositionality of Neural Networks by Decoding Representations to Inputs. NeurIPS Mike Wu, Noah D. Goodman, Stefano Ermon
2021	J	`jnl`	Improving Compositionality of Neural Networks by Decoding Representations to Inputs. CoRR Mike Wu, Noah D. Goodman, Stefano Ermon
2021	J	`jnl`	Modeling Item Response Theory with Stochastic Variational Inference. CoRR Mike Wu, Richard Lee Davis, Benjamin W. Domingue, Chris Piech, Noah D. Goodman
2021	J	`jnl`	Optimizing for Interpretability in Deep Neural Networks with Tree Regularization. J. Artif. Intell. Res. Mike Wu, Sonali Parbhoo, Michael C. Hughes, Volker Roth, Finale Doshi-Velez
2021	J	`jnl`	ProtoTransformer: A Meta-Learning Approach to Providing Student Feedback. CoRR Mike Wu, Noah D. Goodman, Chris Piech, Chelsea Finn
2021	J	`jnl`	Temperature as Uncertainty in Contrastive Learning. CoRR Oliver Zhang, Mike Wu, Jasmine Bayrooti, Noah D. Goodman
2021	J	`jnl`	Tradeoffs Between Contrastive and Supervised Learning: An Empirical Study. CoRR Ananya Karthik, Mike Wu, Noah D. Goodman, Alex Tamkin
2021	A*	`conf`	Viewmaker Networks: Learning Views for Unsupervised Representation Learning. ICLR Alex Tamkin, Mike Wu, Noah D. Goodman
2020	J	`jnl`	A Simple Framework for Uncertainty in Contrastive Learning. CoRR Mike Wu, Noah D. Goodman
2020	J	`jnl`	Conditional Negative Sampling for Contrastive Learning of Visual Representations. CoRR Mike Wu, Milan Mossé, Chengxu Zhuang, Daniel Yamins, Noah D. Goodman
2020	J	`jnl`	HarperValleyBank: A Domain-Specific Spoken Dialog Corpus. CoRR Mike Wu, Jonathan Nafziger, Anthony Scodary, Andrew Maas
2020	A*	`conf`	Meta-Amortized Variational Inference and Learning. AAAI Mike Wu, Kristy Choi, Noah D. Goodman, Stefano Ermon
2020	J	`jnl`	On Mutual Information in Contrastive Learning for Visual Representations. CoRR Mike Wu, Chengxu Zhuang, Milan Mossé, Daniel Yamins, Noah D. Goodman
2020	A*	`conf`	Regional Tree Regularization for Interpretability in Deep Neural Networks. AAAI Mike Wu, Sonali Parbhoo, Michael C. Hughes, Ryan Kindle, Leo A. Celi, Maurizio Zazzi, Volker Roth, Finale Doshi-Velez
2020	B	`conf`	Variational Item Response Theory: Fast, Accurate, and Expressive. EDM Mike Wu, Richard Lee Davis, Benjamin W. Domingue, Chris Piech, Noah D. Goodman
2020	J	`jnl`	Variational Item Response Theory: Fast, Accurate, and Expressive. CoRR Mike Wu, Richard Lee Davis, Benjamin W. Domingue, Chris Piech, Noah D. Goodman
2020	J	`jnl`	Viewmaker Networks: Learning Views for Unsupervised Representation Learning. CoRR Alex Tamkin, Mike Wu, Noah D. Goodman
2019	A	`conf`	Differentiable Antithetic Sampling for Variance Reduction in Stochastic Variational Inference. AISTATS Mike Wu, Noah D. Goodman, Stefano Ermon
2019	J	`jnl`	Generative Grading: Neural Approximate Parsing for Automated Student Feedback. CoRR Ali Malik, Mike Wu, Vrinda Vasavada, Jinpeng Song, John Mitchell, Noah D. Goodman, Chris Piech
2019	J	`jnl`	Gradient Boosting Machine: A Survey. CoRR Zhiyuan He, Danchen Lin, Thomas Lau, Mike Wu
2019	J	`jnl`	Meta-Amortized Variational Inference and Learning. CoRR Kristy Choi, Mike Wu, Noah D. Goodman, Stefano Ermon
2019	J	`jnl`	Multimodal Generative Models for Compositional Representation Learning. CoRR Mike Wu, Noah D. Goodman
2019	J	`jnl`	Optimizing for Interpretability in Deep Neural Networks with Tree Regularization. CoRR Mike Wu, Sonali Parbhoo, Michael C. Hughes, Volker Roth, Finale Doshi-Velez
2019	J	`jnl`	Pragmatic inference and visual abstraction enable contextual flexibility during visual communication. CoRR Judith W. Fan, Robert X. D. Hawkins, Mike Wu, Noah D. Goodman
2019	J	`jnl`	Regional Tree Regularization for Interpretability in Black Box Models. CoRR Mike Wu, Sonali Parbhoo, Michael C. Hughes, Ryan Kindle, Leo A. Celi, Maurizio Zazzi, Volker Roth, Finale Doshi-Velez
2019	A*	`conf`	Zero Shot Learning for Code Education: Rubric Sampling with Deep Learning Inference. AAAI Mike Wu, Milan Mossé, Noah D. Goodman, Chris Piech
2018	A*	`conf`	Beyond Sparsity: Tree Regularization of Deep Models for Interpretability. AAAI Mike Wu, Michael C. Hughes, Sonali Parbhoo, Maurizio Zazzi, Volker Roth, Finale Doshi-Velez
2018	J	`jnl`	Differentiable Antithetic Sampling for Variance Reduction in Stochastic Variational Inference. CoRR Mike Wu, Noah D. Goodman, Stefano Ermon
2018	A*	`conf`	Multimodal Generative Models for Scalable Weakly-Supervised Learning. NeurIPS Mike Wu, Noah D. Goodman
2018	J	`jnl`	Multimodal Generative Models for Scalable Weakly-Supervised Learning. CoRR Mike Wu, Noah D. Goodman
2018	J	`jnl`	Zero Shot Learning for Code Education: Rubric Sampling with Deep Learning Inference. CoRR Mike Wu, Milan Mossé, Noah D. Goodman, Chris Piech
2017	J	`jnl`	Beyond Sparsity: Tree Regularization of Deep Models for Interpretability. CoRR Mike Wu, Michael C. Hughes, Sonali Parbhoo, Maurizio Zazzi, Volker Roth, Finale Doshi-Velez
2017	—	`conf`	Predicting intervention onset in the ICU with switching state space models. CRI Marzyeh Ghassemi, Mike Wu, Michael C. Hughes, Peter Szolovits, Finale Doshi-Velez
2017	J	`jnl`	Understanding vasopressor intervention and weaning: risk prediction in a public heterogeneous clinical time series database. J. Am. Medical Informatics Assoc. Mike Wu, Marzyeh Ghassemi, Mengling Feng, Leo A. Celi, Peter Szolovits, Finale Doshi-Velez
2016	J	`jnl`	Position and Vector Detection of Blind Spot motion with the Horn-Schunck Optical Flow. CoRR Stephen Yu, Mike Wu
2016	J	`jnl`	Spreadsheet Probabilistic Programming. CoRR Mike Wu, Yura N. Perov, Frank D. Wood, Hongseok Yang
2015	J	`jnl`	Financial Market Prediction. CoRR Mike Wu
2012	—	`conf`	Towards Ease of Building Legos in Assessing eHealth Language Technologies A RESTful Laboratory for Data and Software. CLEF (Online Working Notes/Labs/Workshop) Hanna Suominen, Karl Kreiner, Mike Wu, Leif Hanlen
2010	A	`conf`	Field evaluation of a collaborative memory aid for persons with amnesia and their family members. ASSETS Mike Wu, Ronald M. Baecker, Brian Richards
2009	A*	`conf`	An exploration of social requirements for exercise group formation. CHI Mike Wu, Abhishek Ranjan, Khai N. Truong
2008	A*	`conf`	Collaborating to remember: a distributed cognition account of families coping with memory impairments. CHI Mike Wu, Jeremy P. Birnholtz, Brian Richards, Ronald Baecker, Michael Massimi
2008	J	`jnl`	Lifelong Interactions - Memory impairment is a family affair. Interactions Mike Wu
2006	—	`conf`	A study of hand shape use in tabletop gesture interaction. CHI Extended Abstracts Julien Epps, Serge Lichman, Mike Wu
2006	—	`conf`	Gesture Registration, Relaxation, and Reuse for Multi-Point Direct-Touch Surfaces. Tabletop Mike Wu, Chia Shen, Kathy Ryall, Clifton Forlines, Ravin Balakrishnan
2006	J	`jnl`	Informing the Design of Direct-Touch Tabletops. IEEE Computer Graphics and Applications Chia Shen, Kathy Ryall, Clifton Forlines, Alan Esenther, Frédéric Vernier, Katherine Everitt, Mike Wu, Daniel Wigdor, Meredith Ringel Morris, Mark S. Hancock, Edward Tse
2006	—	`conf`	ViCAT: Visualisation and Interaction on a Collaborative Access Table. Tabletop Fang Chen, Peter Eades, Julien Epps, Serge Lichman, Benjamin Close, Peter Hutterer, Masahiro Takatsuka, Bruce H. Thomas, Mike Wu
2005	B	`conf`	A study of manual gesture-based selection for the PEMMI multimodal transport management interface. ICMI Fang Chen, Eric H. C. Choi, Julien Epps, Serge Lichman, Natalie Ruiz, Yu (David) Shi, Ronnie Taib, Mike Wu
2005	A*	`conf`	Participatory design of an orientation aid for amnesics. CHI Mike Wu, Ronald Baecker, Brian Richards
2005	B	`conf`	Under My Finger: Human Factors in Pushing and Rotating Documents Across the Table. INTERACT Clifton Forlines, Chia Shen, Frédéric Vernier, Mike Wu
2004	—	`conf`	Participatory design with individuals who have amnesia. PDC Mike Wu, Brian Richards, Ronald Baecker
2003	—	`conf`	Decomposition of speech into voiced and unvoiced components based on a state-space signal model. ICASSP (1) Mark Thomson, Simon Boland, Mike Wu, Julien Epps, Michael Smithers
2003	A*	`conf`	Multi-finger and whole hand gestural interaction techniques for multi-user tabletop displays. UIST Mike Wu, Ravin Balakrishnan
2003	—	`conf`	Primeclimb: Designing to Facilitate Mediated Collaborative Inquiry. CSCL James Dai, Mike Wu, Jonathan Cohen, Maria M. Klawe