default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDMike Wu
Person information
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
Books and Theses
- 2022
[b1]Mike Wu:
Extensions and applications of deep probabilistic inference for generative models. Stanford University, USA, 2022
Journal Articles
- 2021
- [j4]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: 1-37 (2021) - 2017
- [j3]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): 488-495 (2017) - 2008
- [j2]Mike Wu:
Lifelong Interactions - Memory impairment is a family affair. Interactions 15(5): 21-23 (2008) - 2006
- [j1]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): 36-46 (2006)
Conference and Workshop Papers
- 2022
- [c27]Mike Wu, Noah D. Goodman:
Foundation Posteriors for Approximate Probabilistic Inference. NeurIPS 2022 - 2021
- [c26]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 - [c25]Alex Tamkin, Mike Wu, Noah D. Goodman:
Viewmaker Networks: Learning Views for Unsupervised Representation Learning. ICLR 2021 - [c24]Mike Wu, Milan Mosse, Chengxu Zhuang, Daniel Yamins, Noah D. Goodman:
Conditional Negative Sampling for Contrastive Learning of Visual Representations. ICLR 2021 - [c23]Mike Wu, Noah D. Goodman, Stefano Ermon:
Improving Compositionality of Neural Networks by Decoding Representations to Inputs. NeurIPS 2021: 26689-26700 - 2020
- [c22]Mike Wu, Kristy Choi, Noah D. Goodman, Stefano Ermon:
Meta-Amortized Variational Inference and Learning. AAAI 2020: 6404-6412 - [c21]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: 6413-6421 - [c20]Mike Wu, Richard Lee Davis, Benjamin W. Domingue, Chris Piech, Noah D. Goodman:
Variational Item Response Theory: Fast, Accurate, and Expressive. EDM 2020 - 2019
- [c19]Mike Wu, Milan Mosse, Noah D. Goodman, Chris Piech:
Zero Shot Learning for Code Education: Rubric Sampling with Deep Learning Inference. AAAI 2019: 782-790 - [c18]Mike Wu, Noah D. Goodman, Stefano Ermon:
Differentiable Antithetic Sampling for Variance Reduction in Stochastic Variational Inference. AISTATS 2019: 2877-2886 - 2018
- [c17]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: 1670-1678 - [c16]Mike Wu, Noah D. Goodman:
Multimodal Generative Models for Scalable Weakly-Supervised Learning. NeurIPS 2018: 5580-5590 - 2017
- [c15]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 - 2012
- [c14]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 - 2010
- [c13]Mike Wu, Ronald M. Baecker, Brian Richards:
Field evaluation of a collaborative memory aid for persons with amnesia and their family members. ASSETS 2010: 51-58 - 2009
- [c12]Mike Wu, Abhishek Ranjan, Khai N. Truong:
An exploration of social requirements for exercise group formation. CHI 2009: 79-82 - 2008
- [c11]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: 825-834 - 2006
- [c10]Julien Epps, Serge Lichman, Mike Wu:
A study of hand shape use in tabletop gesture interaction. CHI Extended Abstracts 2006: 748-753 - [c9]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: 59-62 - [c8]Mike Wu, Chia Shen, Kathy Ryall, Clifton Forlines, Ravin Balakrishnan:
Gesture Registration, Relaxation, and Reuse for Multi-Point Direct-Touch Surfaces. Tabletop 2006: 185-192 - 2005
- [c7]Mike Wu, Ronald Baecker, Brian Richards:
Participatory design of an orientation aid for amnesics. CHI 2005: 511-520 - [c6]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: 274-281 - [c5]Clifton Forlines, Chia Shen, Frédéric Vernier, Mike Wu:
Under My Finger: Human Factors in Pushing and Rotating Documents Across the Table. INTERACT 2005: 994-997 - 2004
- [c4]Mike Wu, Brian Richards, Ronald Baecker:
Participatory design with individuals who have amnesia. PDC 2004: 214-223 - 2003
- [c3]James Dai, Mike Wu, Jonathan Cohen, Maria M. Klawe:
Primeclimb: Designing to Facilitate Mediated Collaborative Inquiry. CSCL 2003: 31-35 - [c2]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: 160-163 - [c1]Mike Wu, Ravin Balakrishnan:
Multi-finger and whole hand gestural interaction techniques for multi-user tabletop displays. UIST 2003: 193-202
Informal and Other Publications
- 2022
- [i29]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 abs/2201.06811 (2022) - [i28]Rose E. Wang, Mike Wu, Noah D. Goodman:
Know Thy Student: Interactive Learning with Gaussian Processes. CoRR abs/2204.12072 (2022) - [i27]Mike Wu, Will McTighe:
Constant Power Root Market Makers. CoRR abs/2205.07452 (2022) - [i26]Mike Wu, Noah D. Goodman:
Foundation Posteriors for Approximate Probabilistic Inference. CoRR abs/2205.09735 (2022) - 2021
- [i25]Mike Wu, Noah D. Goodman, Stefano Ermon:
Improving Compositionality of Neural Networks by Decoding Representations to Inputs. CoRR abs/2106.00769 (2021) - [i24]Mike Wu, Noah D. Goodman, Chris Piech, Chelsea Finn:
ProtoTransformer: A Meta-Learning Approach to Providing Student Feedback. CoRR abs/2107.14035 (2021) - [i23]Mike Wu, Richard Lee Davis, Benjamin W. Domingue, Chris Piech, Noah D. Goodman:
Modeling Item Response Theory with Stochastic Variational Inference. CoRR abs/2108.11579 (2021) - [i22]Oliver Zhang, Mike Wu, Jasmine Bayrooti, Noah D. Goodman:
Temperature as Uncertainty in Contrastive Learning. CoRR abs/2110.04403 (2021) - [i21]Ananya Karthik, Mike Wu, Noah D. Goodman, Alex Tamkin:
Tradeoffs Between Contrastive and Supervised Learning: An Empirical Study. CoRR abs/2112.05340 (2021) - 2020
- [i20]Mike Wu, Richard Lee Davis, Benjamin W. Domingue, Chris Piech, Noah D. Goodman:
Variational Item Response Theory: Fast, Accurate, and Expressive. CoRR abs/2002.00276 (2020) - [i19]Mike Wu, Chengxu Zhuang, Milan Mosse, Daniel Yamins, Noah D. Goodman:
On Mutual Information in Contrastive Learning for Visual Representations. CoRR abs/2005.13149 (2020) - [i18]Mike Wu, Milan Mosse, Chengxu Zhuang, Daniel Yamins, Noah D. Goodman:
Conditional Negative Sampling for Contrastive Learning of Visual Representations. CoRR abs/2010.02037 (2020) - [i17]Mike Wu, Noah D. Goodman:
A Simple Framework for Uncertainty in Contrastive Learning. CoRR abs/2010.02038 (2020) - [i16]Alex Tamkin, Mike Wu, Noah D. Goodman:
Viewmaker Networks: Learning Views for Unsupervised Representation Learning. CoRR abs/2010.07432 (2020) - [i15]Mike Wu, Jonathan Nafziger, Anthony Scodary, Andrew Maas:
HarperValleyBank: A Domain-Specific Spoken Dialog Corpus. CoRR abs/2010.13929 (2020) - 2019
- [i14]Kristy Choi, Mike Wu, Noah D. Goodman, Stefano Ermon:
Meta-Amortized Variational Inference and Learning. CoRR abs/1902.01950 (2019) - [i13]Judith W. Fan, Robert X. D. Hawkins, Mike Wu, Noah D. Goodman:
Pragmatic inference and visual abstraction enable contextual flexibility during visual communication. CoRR abs/1903.04448 (2019) - [i12]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 abs/1905.09916 (2019) - [i11]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 abs/1908.04494 (2019) - [i10]Mike Wu, Sonali Parbhoo, Michael C. Hughes, Volker Roth, Finale Doshi-Velez:
Optimizing for Interpretability in Deep Neural Networks with Tree Regularization. CoRR abs/1908.05254 (2019) - [i9]Zhiyuan He, Danchen Lin, Thomas Lau, Mike Wu:
Gradient Boosting Machine: A Survey. CoRR abs/1908.06951 (2019) - [i8]Mike Wu, Noah D. Goodman:
Multimodal Generative Models for Compositional Representation Learning. CoRR abs/1912.05075 (2019) - 2018
- [i7]Mike Wu, Noah D. Goodman:
Multimodal Generative Models for Scalable Weakly-Supervised Learning. CoRR abs/1802.05335 (2018) - [i6]Mike Wu, Milan Mosse, Noah D. Goodman, Chris Piech:
Zero Shot Learning for Code Education: Rubric Sampling with Deep Learning Inference. CoRR abs/1809.01357 (2018) - [i5]Mike Wu, Noah D. Goodman, Stefano Ermon:
Differentiable Antithetic Sampling for Variance Reduction in Stochastic Variational Inference. CoRR abs/1810.02555 (2018) - 2017
- [i4]Mike Wu, Michael C. Hughes, Sonali Parbhoo, Maurizio Zazzi, Volker Roth, Finale Doshi-Velez:
Beyond Sparsity: Tree Regularization of Deep Models for Interpretability. CoRR abs/1711.06178 (2017) - 2016
- [i3]Stephen Yu, Mike Wu:
Position and Vector Detection of Blind Spot motion with the Horn-Schunck Optical Flow. CoRR abs/1603.07625 (2016) - [i2]Mike Wu, Yura N. Perov, Frank D. Wood, Hongseok Yang:
Spreadsheet Probabilistic Programming. CoRR abs/1606.04216 (2016) - 2015
- [i1]Mike Wu:
Financial Market Prediction. CoRR abs/1503.02328 (2015)
Coauthor Index
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from 
to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the 
of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from 
, 
, and 
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from 
.
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-05-08 21:54 CEST by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
