Mike Wu

Publication Activity (10 Years)

Years Active: 2003-2022
Publications (10 Years): 43

Top Topics

Variational Inference

Visual Representations

Gaussian Processes

Top Venues

Publications

Rose E. Wang, Mike Wu, Noah D. Goodman
Know Thy Student: Interactive Learning with Gaussian Processes. CoRR (2022)
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
Tutela: An Open-Source Tool for Assessing User-Privacy on Ethereum and Tornado Cash. CoRR (2022)
Mike Wu, Noah D. Goodman
Foundation Posteriors for Approximate Probabilistic Inference. NeurIPS (2022)
Mike Wu, Will McTighe
Constant Power Root Market Makers. CoRR (2022)
Mike Wu, Noah D. Goodman
Foundation Posteriors for Approximate Probabilistic Inference. CoRR (2022)
Mike Wu, Noah D. Goodman, Stefano Ermon
Improving Compositionality of Neural Networks by Decoding Representations to Inputs. CoRR (2021)
Mike Wu, Noah D. Goodman, Chris Piech, Chelsea Finn
ProtoTransformer: A Meta-Learning Approach to Providing Student Feedback. CoRR (2021)
Mike Wu, Milan Mosse, Chengxu Zhuang, Daniel Yamins, Noah D. Goodman
Conditional Negative Sampling for Contrastive Learning of Visual Representations. ICLR (2021)
Alex Tamkin, Mike Wu, Noah D. Goodman
Viewmaker Networks: Learning Views for Unsupervised Representation Learning. ICLR (2021)
Oliver Zhang, Mike Wu, Jasmine Bayrooti, Noah D. Goodman
Temperature as Uncertainty in Contrastive Learning. CoRR (2021)
Ali Malik, Mike Wu, Vrinda Vasavada, Jinpeng Song, Madison Coots, John Mitchell, Noah D. Goodman, Chris Piech
Generative Grading: Near Human-level Accuracy for Automated Feedback on Richly Structured Problems. EDM (2021)
Mike Wu, Richard Lee Davis, Benjamin W. Domingue, Chris Piech, Noah D. Goodman
Modeling Item Response Theory with Stochastic Variational Inference. CoRR (2021)
Mike Wu, Noah D. Goodman, Stefano Ermon
Improving Compositionality of Neural Networks by Decoding Representations to Inputs. NeurIPS (2021)
Mike Wu, Sonali Parbhoo, Michael C. Hughes, Volker Roth, Finale Doshi-Velez
Optimizing for Interpretability in Deep Neural Networks with Tree Regularization. J. Artif. Intell. Res. 72 (2021)
Ananya Karthik, Mike Wu, Noah D. Goodman, Alex Tamkin
Tradeoffs Between Contrastive and Supervised Learning: An Empirical Study. CoRR (2021)
Alex Tamkin, Mike Wu, Noah D. Goodman
Viewmaker Networks: Learning Views for Unsupervised Representation Learning. CoRR (2020)
Mike Wu, Milan Mosse, Chengxu Zhuang, Daniel Yamins, Noah D. Goodman
Conditional Negative Sampling for Contrastive Learning of Visual Representations. CoRR (2020)
Mike Wu, Noah D. Goodman
A Simple Framework for Uncertainty in Contrastive Learning. CoRR (2020)
Mike Wu, Richard Lee Davis, Benjamin W. Domingue, Chris Piech, Noah D. Goodman
Variational Item Response Theory: Fast, Accurate, and Expressive. CoRR (2020)
Mike Wu, Jonathan Nafziger, Anthony Scodary, Andrew Maas
HarperValleyBank: A Domain-Specific Spoken Dialog Corpus. CoRR (2020)
Mike Wu, Sonali Parbhoo, Michael C. Hughes, Ryan Kindle, Leo A. Celi, Maurizio Zazzi, Volker Roth, Finale Doshi-Velez
Regional Tree Regularization for Interpretability in Deep Neural Networks. AAAI (2020)
Mike Wu, Chengxu Zhuang, Milan Mosse, Daniel Yamins, Noah D. Goodman
On Mutual Information in Contrastive Learning for Visual Representations. CoRR (2020)
Mike Wu, Richard Lee Davis, Benjamin W. Domingue, Chris Piech, Noah D. Goodman
Variational Item Response Theory: Fast, Accurate, and Expressive. EDM (2020)
Mike Wu, Kristy Choi, Noah D. Goodman, Stefano Ermon
Meta-Amortized Variational Inference and Learning. AAAI (2020)
Mike Wu, Sonali Parbhoo, Michael C. Hughes, Volker Roth, Finale Doshi-Velez
Optimizing for Interpretability in Deep Neural Networks with Tree Regularization. CoRR (2019)
Mike Wu, Milan Mosse, Noah D. Goodman, Chris Piech
Zero Shot Learning for Code Education: Rubric Sampling with Deep Learning Inference. AAAI (2019)
Ali Malik, Mike Wu, Vrinda Vasavada, Jinpeng Song, John Mitchell, Noah D. Goodman, Chris Piech
Generative Grading: Neural Approximate Parsing for Automated Student Feedback. CoRR (2019)
Kristy Choi, Mike Wu, Noah D. Goodman, Stefano Ermon
Meta-Amortized Variational Inference and Learning. CoRR (2019)
Judith W. Fan, Robert X. D. Hawkins, Mike Wu, Noah D. Goodman
Pragmatic inference and visual abstraction enable contextual flexibility during visual communication. CoRR (2019)
Mike Wu, Noah D. Goodman
Multimodal Generative Models for Compositional Representation Learning. CoRR (2019)
Mike Wu, Sonali Parbhoo, Michael C. Hughes, Ryan Kindle, Leo A. Celi, Maurizio Zazzi, Volker Roth, Finale Doshi-Velez
Regional Tree Regularization for Interpretability in Black Box Models. CoRR (2019)
Mike Wu, Noah D. Goodman, Stefano Ermon
Differentiable Antithetic Sampling for Variance Reduction in Stochastic Variational Inference. AISTATS (2019)
Zhiyuan He, Danchen Lin, Thomas Lau, Mike Wu
Gradient Boosting Machine: A Survey. CoRR (2019)
Mike Wu, Milan Mosse, Noah D. Goodman, Chris Piech
Zero Shot Learning for Code Education: Rubric Sampling with Deep Learning Inference. CoRR (2018)
Mike Wu, Noah D. Goodman
Multimodal Generative Models for Scalable Weakly-Supervised Learning. NeurIPS (2018)
Mike Wu, Michael C. Hughes, Sonali Parbhoo, Maurizio Zazzi, Volker Roth, Finale Doshi-Velez
Beyond Sparsity: Tree Regularization of Deep Models for Interpretability. AAAI (2018)
Mike Wu, Noah D. Goodman
Multimodal Generative Models for Scalable Weakly-Supervised Learning. CoRR (2018)
Mike Wu, Noah D. Goodman, Stefano Ermon
Differentiable Antithetic Sampling for Variance Reduction in Stochastic Variational Inference. CoRR (2018)
Mike Wu, Marzyeh Ghassemi, Mengling Feng, Leo A. Celi, Peter Szolovits, Finale Doshi-Velez
Understanding vasopressor intervention and weaning: risk prediction in a public heterogeneous clinical time series database. J. Am. Medical Informatics Assoc. 24 (3) (2017)
Mike Wu, Michael C. Hughes, Sonali Parbhoo, Maurizio Zazzi, Volker Roth, Finale Doshi-Velez
Beyond Sparsity: Tree Regularization of Deep Models for Interpretability. CoRR (2017)
Marzyeh Ghassemi, Mike Wu, Michael C. Hughes, Peter Szolovits, Finale Doshi-Velez
Predicting intervention onset in the ICU with switching state space models. CRI (2017)
Stephen Yu, Mike Wu
Position and Vector Detection of Blind Spot motion with the Horn-Schunck Optical Flow. CoRR (2016)
Mike Wu, Yura N. Perov, Frank D. Wood, Hongseok Yang
Spreadsheet Probabilistic Programming. CoRR (2016)
Mike Wu
Financial Market Prediction. CoRR (2015)
Hanna Suominen, Karl Kreiner, Mike Wu, Leif Hanlen
Towards Ease of Building Legos in Assessing eHealth Language Technologies A RESTful Laboratory for Data and Software. CLEF (Online Working Notes/Labs/Workshop) (2012)
Mike Wu, Ronald M. Baecker, Brian Richards
Field evaluation of a collaborative memory aid for persons with amnesia and their family members. ASSETS (2010)
Mike Wu, Abhishek Ranjan, Khai N. Truong
An exploration of social requirements for exercise group formation. CHI (2009)
Mike Wu
Lifelong Interactions - Memory impairment is a family affair. Interactions 15 (5) (2008)
Mike Wu, Jeremy P. Birnholtz, Brian Richards, Ronald Baecker, Michael Massimi
Collaborating to remember: a distributed cognition account of families coping with memory impairments. CHI (2008)
Chia Shen, Kathy Ryall, Clifton Forlines, Alan Esenther, Frédéric Vernier, Katherine Everitt, Mike Wu, Daniel Wigdor, Meredith Ringel Morris, Mark S. Hancock, Edward Tse
Informing the Design of Direct-Touch Tabletops. IEEE Computer Graphics and Applications 26 (5) (2006)
Fang Chen, Peter Eades, Julien Epps, Serge Lichman, Benjamin Close, Peter Hutterer, Masahiro Takatsuka, Bruce H. Thomas, Mike Wu
ViCAT: Visualisation and Interaction on a Collaborative Access Table. Tabletop (2006)
Julien Epps, Serge Lichman, Mike Wu
A study of hand shape use in tabletop gesture interaction. CHI Extended Abstracts (2006)
Mike Wu, Chia Shen, Kathy Ryall, Clifton Forlines, Ravin Balakrishnan
Gesture Registration, Relaxation, and Reuse for Multi-Point Direct-Touch Surfaces. Tabletop (2006)
Clifton Forlines, Chia Shen, Frédéric Vernier, Mike Wu
Under My Finger: Human Factors in Pushing and Rotating Documents Across the Table. INTERACT (2005)
Mike Wu, Ronald Baecker, Brian Richards
Participatory design of an orientation aid for amnesics. CHI (2005)
Fang Chen, Eric H. C. Choi, Julien Epps, Serge Lichman, Natalie Ruiz, Yu (David) Shi, Ronnie Taib, Mike Wu
A study of manual gesture-based selection for the PEMMI multimodal transport management interface. ICMI (2005)
Mike Wu, Brian Richards, Ronald Baecker
Participatory design with individuals who have amnesia. PDC (2004)
Mike Wu, Ravin Balakrishnan
Multi-finger and whole hand gestural interaction techniques for multi-user tabletop displays. UIST (2003)
Mark Thomson, Simon Boland, Mike Wu, Julien Epps, Michael Smithers
Decomposition of speech into voiced and unvoiced components based on a state-space signal model. ICASSP (1) (2003)
James Dai, Mike Wu, Jonathan Cohen, Maria M. Klawe
Primeclimb: Designing to Facilitate Mediated Collaborative Inquiry. CSCL (2003)