Jankowiak, Martin

1. Pyro: Deep Universal Probabilistic Programming
   2018/10/18 by Eli Bingham, Bingham, Eli, Jonathan P. Chen +17 · 1 voice · 101 citations
   Computer Science · Mathematics · #Computational Physics and Python Applications #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Generative Adversarial Networks and Image Synthesis #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Programming Languages (cs.PL) #cs.LG #cs.PL #stat.ML
2. Composable Effects for Flexible and Accelerated Probabilistic Programming in NumPyro
   2019/12/24 by Du Phan, Phan, Du, Neeraj Pradhan +3 · 80 citations
   Computer Science · #Parallel Computing and Optimization Techniques #Bayesian Modeling and Causal Inference #Formal Methods in Verification
3. High-Dimensional Bayesian Optimization with Sparse Axis-Aligned Subspaces
   2021/02/27 by David Eriksson, Eriksson, David, Martin Jankowiak +1 · 35 citations
   Computer Science · #Advanced Multi-Objective Optimization Algorithms #Gaussian Processes and Bayesian Inference #Machine Learning and Data Classification
4. Variational Bayesian Optimal Experimental Design
   2019/03/13 by Adam Foster, Foster, Adam, Martin Jankowiak +11 · 21 citations
   Decision Sciences · Computer Science · #Optimal Experimental Design Methods #Advanced Multi-Objective Optimization Algorithms #Probabilistic and Robust Engineering Design
5. A Unified Stochastic Gradient Approach to Designing Bayesian-Optimal Experiments
   2019/11/01 by Adam Foster, Foster, Adam, Martin Jankowiak +7 · 9 citations
   Computer Science · Decision Sciences · #Advanced Multi-Objective Optimization Algorithms #Computation (stat.CO) #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Optimal Experimental Design Methods
6. Functional Tensors for Probabilistic Programming
   2019/10/23 by Fritz Obermeyer, Eli Bingham, Obermeyer, Fritz +7 · 2 citations
   Computer Science · #Bayesian Modeling and Causal Inference #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Algorithms
7. Pathwise Derivatives Beyond the Reparameterization Trick
   2018/06/05 by Martin Jankowiak, Fritz Obermeyer, Jankowiak, Martin +1 · 1 citation
   Computer Science · Physics and Astronomy · #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Model Reduction and Neural Networks #Neural Networks and Applications
8. Tensor Variable Elimination for Plated Factor Graphs
   2019/02/08 by Fritz Obermeyer, Eli Bingham, Obermeyer, Fritz +11 · 1 citation
   Computer Science · Mathematics · #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Matrix Theory and Algorithms #Tensor decomposition and applications
9. Neural Likelihoods for Multi-Output Gaussian Processes
   2019/05/31 by Martin Jankowiak, Jacob R. Gardner, Jankowiak, Martin +1 · 1 citation
   Computer Science · Engineering · #Control Systems and Identification #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Target Tracking and Data Fusion in Sensor Networks
10. Fast Matrix Square Roots with Applications to Gaussian Processes and Bayesian Optimization
    2020/06/19 by Pleiss, Geoff, Jankowiak, Martin, Eriksson, David +2 · 1 citation
    #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
11. Surrogate Likelihoods for Variational Annealed Importance Sampling
    2021/12/22 by Martin Jankowiak, Du Phan, Jankowiak, Martin +1 · 1 citation
    Computer Science · #Bayesian Methods and Mixture Models #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Algorithms
12. Experimental constraints on the free fall acceleration of antimatter
    2009/07/23 by Daniele S. M. Alves, Alves, Daniele S. M., Martin Jankowiak +3 · 1 citation
    Engineering · Physics and Astronomy · #Experimental and Theoretical Physics Studies #FOS: Physical sciences #General Relativity and Quantum Cosmology (gr-qc) #High Energy Physics - Experiment (hep-ex) #High Energy Physics - Phenomenology (hep-ph) #Radioactive Decay and Measurement Techniques #Sports Dynamics and Biomechanics #gr-qc #hep-ex #hep-ph
13. Scalable Cross Validation Losses for Gaussian Process Models
    2021/05/24 by Martin Jankowiak, Geoff Pleiss, Jankowiak, Martin +1 · 2 citations
    Computer Science · #Advanced Multi-Objective Optimization Algorithms #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Data Classification