David A. Knowles

Publication Activity (10 Years)

Years Active: 2007-2024
Publications (10 Years): 15

Top Topics

Textual Information

Variational Inference

Linear Dynamical Systems

Top Venues

IEEE Trans. Pattern Anal. Mach. Intell.

PLoS Comput. Biol.

Publications

Andrew Stirn, David A. Knowles
The VampPrior Mixture Model. CoRR (2024)
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)
Peter Halmos, Jonathan W. Pillow, David A. Knowles
System Identification for Continuous-time Linear Dynamical Systems. CoRR (2023)
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 (2023)
Andrew Stirn, Harm Wessels, Megan Schertzer, Laura Pereira, Neville E. Sanjana, David A. Knowles
Faithful Heteroscedastic Regression with Neural Networks. AISTATS (2023)
Rockwell J. Weiner, Chirag M. Lakhani, David A. Knowles, Gamze Gürsoy
LDmat: efficiently queryable compression of linkage disequilibrium matrices. Bioinform. 39 (2) (2023)
Keren Isaev, David A. Knowles
Investigating RNA splicing as a source of cellular diversity using a binomial mixture model. MLCB (2023)
Stephen Malina, Daniel Cizin, David A. Knowles
Deep mendelian randomization: Investigating the causal knowledge of genomic deep learning models. PLoS Comput. Biol. 18 (10) (2022)
Andrew Stirn, Hans-Hermann Wessels, Megan Schertzer, Laura Pereira, Neville E. Sanjana, David A. Knowles
Faithful Heteroscedastic Regression with Neural Networks. CoRR (2022)
Udai G. Nagpal, David A. Knowles
Active Learning in CNNs via Expected Improvement Maximization. CoRR (2020)
Andrew Stirn, David A. Knowles
Variational Variance: Simple and Reliable Predictive Variance Parameterization. CoRR (2020)
Andrew Stirn, Tony Jebara, David A. Knowles
A New Distribution on the Simplex with Auto-Encoding Applications. CoRR (2019)
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)
Andrew Stirn, Tony Jebara, David A. Knowles
A New Distribution on the Simplex with Auto-Encoding Applications. NeurIPS (2019)
Konstantina Palla, David A. Knowles, Zoubin Ghahramani
A Birth-Death Process for Feature Allocation. ICML (2017)
David A. Knowles, Zoubin Ghahramani
Pitman Yor Diffusion Trees for Bayesian Hierarchical Clustering. IEEE Trans. Pattern Anal. Mach. Intell. 37 (2) (2015)
Amar Shah, David A. Knowles, Zoubin Ghahramani
An Empirical Study of Stochastic Variational Inference Algorithms for the Beta Bernoulli Process. ICML (2015)
Amar Shah, David A. Knowles, Zoubin Ghahramani
An Empirical Study of Stochastic Variational Algorithms for the Beta Bernoulli Process. CoRR (2015)
Kien Nguyen, Jörg Bredno, David A. Knowles
Using contextual information to classify nuclei in histology images. ISBI (2015)
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) (2015)
David A. Knowles, Zoubin Ghahramani, Konstantina Palla
A reversible infinite HMM using normalised random measures. ICML (2014)
Creighton Heaukulani, David A. Knowles, Zoubin Ghahramani
Beta Diffusion Trees. ICML (2014)
Novi Quadrianto, Viktoriia Sharmanska, David A. Knowles, Zoubin Ghahramani
The Supervised IBP: Neighbourhood Preserving Infinite Latent Feature Models. CoRR (2013)
Novi Quadrianto, Viktoriia Sharmanska, David A. Knowles, Zoubin Ghahramani
The Supervised IBP: Neighbourhood Preserving Infinite Latent Feature Models. UAI (2013)
Tim Salimans, David A. Knowles
Fixed-Form Variational Posterior Approximation through Stochastic Linear Regression CoRR (2012)
Andrew Gordon Wilson, David A. Knowles, Zoubin Ghahramani
Gaussian Process Regression Networks. ICML (2012)
Konstantina Palla, David A. Knowles, Zoubin Ghahramani
An Infinite Latent Attribute Model for Network Data. ICML (2012)
David A. Knowles, Konstantina Palla, Zoubin Ghahramani
A nonparametric variable clustering model. NIPS (2012)
David A. Knowles, Jurgen Van Gael, Zoubin Ghahramani
Message Passing Algorithms for the Dirichlet Diffusion Tree. ICML (2011)
David A. Knowles, Zoubin Ghahramani
Pitman-Yor Diffusion Trees. UAI (2011)
David A. Knowles, Tom Minka
Non-conjugate Variational Message Passing for Multinomial and Binary Regression. NIPS (2011)
David A. Knowles, Zoubin Ghahramani
Nonparametric Bayesian Sparse Factor Models with application to Gene Expression modelling CoRR (2010)
Finale Doshi-Velez, David A. Knowles, Shakir Mohamed, Zoubin Ghahramani
Large Scale Nonparametric Bayesian Inference: Data Parallelisation in the Indian Buffet Process. NIPS (2009)
David A. Knowles, Zoubin Ghahramani
Infinite Sparse Factor Analysis and Infinite Independent Components Analysis. ICA (2007)