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ORCIDDavid A. Knowles
Person information
- affiliation: New York Genome Center, New York City, NY, USA
- affiliation: Columbia University, New York City, NY, USA
- affiliation: Stanford University, Department of Computer Science, Stanford, CA, USA
- affiliation (PhD): University of Cambridge, Department of Engineering , UK
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2020 – today
- 2024
[c18]Cameron Park, Shouvik Mani, Nicolas Beltran-Velez, Katie Maurer, Satyen Gohil, Shuqiang Li, Teddy Huang, David A. Knowles, Catherine J. Wu, Elham Azizi:
DIISCO: A Bayesian Framework for Inferring Dynamic Intercellular Interactions from Time-Series Single-Cell Data. RECOMB 2024: 390-395- [i11]Andrew Stirn, David A. Knowles:
The VampPrior Mixture Model. CoRR abs/2402.04412 (2024) - 2023
- [j5]Rockwell J. Weiner, Chirag M. Lakhani, David A. Knowles
, Gamze Gürsoy:
LDmat: efficiently queryable compression of linkage disequilibrium matrices. Bioinform. 39(2) (2023) - [c17]Andrew Stirn, Harm Wessels, Megan Schertzer, Laura Pereira, Neville E. Sanjana, David A. Knowles:
Faithful Heteroscedastic Regression with Neural Networks. AISTATS 2023: 5593-5613 - [c16]Keren Isaev, David A. Knowles:
Investigating RNA splicing as a source of cellular diversity using a binomial mixture model. MLCB 2023: 163-175 - [e3]David A. Knowles, Sara Mostafavi:
Machine Learning in Computational Biology, November 30 - December 1, 2023, Seattle, WA, USA. Proceedings of Machine Learning Research 240, PMLR 2023 [contents] - [i10]Daniel H. Um, David A. Knowles, Gail E. Kaiser:
Vector Embeddings by Sequence Similarity and Context for Improved Compression, Similarity Search, Clustering, Organization, and Manipulation of cDNA Libraries. CoRR abs/2308.05118 (2023) - [i9]Peter Halmos, Jonathan W. Pillow, David A. Knowles:
System Identification for Continuous-time Linear Dynamical Systems. CoRR abs/2308.11933 (2023) - 2022
- [j4]Stephen Malina, Daniel Cizin, David A. Knowles:
Deep mendelian randomization: Investigating the causal knowledge of genomic deep learning models. PLoS Comput. Biol. 18(10): 1009880 (2022) - [e2]David A. Knowles, Sara Mostafavi, Su-In Lee:
Machine Learning in Computational Biology, 21-22 November 2022, Online. Proceedings of Machine Learning Research 200, PMLR 2022 [contents] - [i8]Andrew Stirn, Hans-Hermann Wessels, Megan Schertzer, Laura Pereira, Neville E. Sanjana, David A. Knowles:
Faithful Heteroscedastic Regression with Neural Networks. CoRR abs/2212.09184 (2022) - 2021
- [e1]David A. Knowles, Sara Mostafavi, Su-In Lee:
Machine Learning in Computational Biology Meeting, MLCB 2021, online, November 22-23, 2021. Proceedings of Machine Learning Research 165, PMLR 2021 [contents] - 2020
- [i7]Andrew Stirn, David A. Knowles:
Variational Variance: Simple and Reliable Predictive Variance Parameterization. CoRR abs/2006.04910 (2020) - [i6]Udai G. Nagpal, David A. Knowles:
Active Learning in CNNs via Expected Improvement Maximization. CoRR abs/2011.14015 (2020)
2010 – 2019
- 2019
- [j3]David A. Knowles, Gina Bouchard, Sylvia K. Plevritis:
Sparse discriminative latent characteristics for predicting cancer drug sensitivity from genomic features. PLoS Comput. Biol. 15(5) (2019) - [c15]Andrew Stirn, Tony Jebara, David A. Knowles:
A New Distribution on the Simplex with Auto-Encoding Applications. NeurIPS 2019: 13670-13680 - [i5]Andrew Stirn, Tony Jebara, David A. Knowles:
A New Distribution on the Simplex with Auto-Encoding Applications. CoRR abs/1905.12052 (2019) - 2017
- [c14]Konstantina Palla, David A. Knowles, Zoubin Ghahramani:
A Birth-Death Process for Feature Allocation. ICML 2017: 2751-2759 - 2015
- [j2]David A. Knowles, Zoubin Ghahramani:
Pitman Yor Diffusion Trees for Bayesian Hierarchical Clustering. IEEE Trans. Pattern Anal. Mach. Intell. 37(2): 271-289 (2015) - [j1]Konstantina Palla, David A. Knowles, Zoubin Ghahramani:
Relational Learning and Network Modelling Using Infinite Latent Attribute Models. IEEE Trans. Pattern Anal. Mach. Intell. 37(2): 462-474 (2015) - [c13]Amar Shah, David A. Knowles, Zoubin Ghahramani:
An Empirical Study of Stochastic Variational Inference Algorithms for the Beta Bernoulli Process. ICML 2015: 1594-1603 - [c12]Kien Nguyen, Jörg Bredno, David A. Knowles:
Using contextual information to classify nuclei in histology images. ISBI 2015: 995-998 - [i4]Amar Shah, David A. Knowles, Zoubin Ghahramani:
An Empirical Study of Stochastic Variational Algorithms for the Beta Bernoulli Process. CoRR abs/1506.08180 (2015) - 2014
- [c11]Creighton Heaukulani, David A. Knowles, Zoubin Ghahramani:
Beta Diffusion Trees. ICML 2014: 1809-1817 - [c10]David A. Knowles, Zoubin Ghahramani, Konstantina Palla:
A reversible infinite HMM using normalised random measures. ICML 2014: 1998-2006 - 2013
- [c9]Novi Quadrianto, Viktoriia Sharmanska, David A. Knowles, Zoubin Ghahramani:
The Supervised IBP: Neighbourhood Preserving Infinite Latent Feature Models. UAI 2013 - [i3]Novi Quadrianto, Viktoriia Sharmanska, David A. Knowles, Zoubin Ghahramani:
The Supervised IBP: Neighbourhood Preserving Infinite Latent Feature Models. CoRR abs/1309.6858 (2013) - 2012
- [c8]Konstantina Palla, David A. Knowles, Zoubin Ghahramani:
An Infinite Latent Attribute Model for Network Data. ICML 2012 - [c7]Andrew Gordon Wilson, David A. Knowles, Zoubin Ghahramani:
Gaussian Process Regression Networks. ICML 2012 - [c6]David A. Knowles, Konstantina Palla, Zoubin Ghahramani:
A nonparametric variable clustering model. NIPS 2012: 2996-3004 - [i2]Tim Salimans, David A. Knowles:
Fixed-Form Variational Posterior Approximation through Stochastic Linear Regression. CoRR abs/1206.6679 (2012) - 2011
- [c5]David A. Knowles, Jurgen Van Gael, Zoubin Ghahramani:
Message Passing Algorithms for the Dirichlet Diffusion Tree. ICML 2011: 721-728 - [c4]David A. Knowles, Tom Minka:
Non-conjugate Variational Message Passing for Multinomial and Binary Regression. NIPS 2011: 1701-1709 - [c3]David A. Knowles, Zoubin Ghahramani:
Pitman-Yor Diffusion Trees. UAI 2011: 410-418 - 2010
- [i1]David A. Knowles, Zoubin Ghahramani:
Nonparametric Bayesian Sparse Factor Models with application to Gene Expression modelling. CoRR abs/1011.6293 (2010)
2000 – 2009
- 2009
- [c2]Finale Doshi-Velez, David A. Knowles, Shakir Mohamed, Zoubin Ghahramani:
Large Scale Nonparametric Bayesian Inference: Data Parallelisation in the Indian Buffet Process. NIPS 2009: 1294-1302 - 2007
- [c1]David A. Knowles, Zoubin Ghahramani:
Infinite Sparse Factor Analysis and Infinite Independent Components Analysis. ICA 2007: 381-388
Coauthor Index
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