Knowles, David A.

1. Gaussian Process Regression Networks
   2011/10/19 by Andrew Gordon Wilson, Wilson, Andrew Gordon, David A. Knowles +3 · 19 citations
   Computer Science · Engineering · #Gaussian Processes and Bayesian Inference #Control Systems and Identification #Fault Detection and Control Systems
2. Faithful Heteroscedastic Regression with Neural Networks
   2022/12/18 by Andrew Stirn, Hans‐Hermann Wessels, Stirn, Andrew +9 · 9 citations
   Computer Science · #Gaussian Processes and Bayesian Inference #Machine Learning and Data Classification #Neural Networks and Applications
3. Stochastic gradient variational Bayes for gamma approximating distributions
   2015/09/04 by David A. Knowles, Knowles, David A. · 6 citations
   Computer Science · Mathematics · #Bayesian Methods and Mixture Models #FOS: Computer and information sciences #Machine Learning (stat.ML) #Statistical Methods and Bayesian Inference #Statistical Methods and Inference
4. Interpretable Neural ODEs for Gene Regulatory Network Discovery under Perturbations
   2025/01/05 by Zaikang Lin, Sei Chang, Lin, Zaikang +11 · 1 voice · 6 citations
   Biochemistry, Genetics and Molecular Biology · #Gene Regulatory Network Analysis #cs.AI #cs.CE #cs.LG #q-bio.MN #stat.ME
5. On Using Control Variates with Stochastic Approximation for Variational Bayes and its Connection to Stochastic Linear Regression
   2014/01/06 by Salimans, Tim, Knowles, David A. · 1 citation
   #Computation (stat.CO) #FOS: Computer and information sciences
6. The Supervised IBP: Neighbourhood Preserving Infinite Latent Feature\n Models
   2013/09/26 by Novi Quadrianto, Quadrianto, Novi, Viktoriia Sharmanska +5 · 3 citations
   Computer Science · #Topic Modeling #Natural Language Processing Techniques #Machine Learning and Data Classification
7. Variational Variance: Simple, Reliable, Calibrated Heteroscedastic Noise Variance Parameterization
   2020/06/08 by Andrew Stirn, Stirn, Andrew, David A. Knowles +1 · 1 citation
   Computer Science · Physics and Astronomy · #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Generative Adversarial Networks and Image Synthesis #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Model Reduction and Neural Networks
8. Disentangling Interpretable Factors with Supervised Independent Subspace Principal Component Analysis
   2024/10/31 by Su, Jiayu, Knowles, David A., Rabadan, Raul · 1 citation
   #FOS: Biological sciences #FOS: Computer and information sciences #Genomics (q-bio.GN) #Machine Learning (cs.LG) #Machine Learning (stat.ML)