Exploiting compositionality to explore a large space of model structures

16 October 2012

William T. Freeman

Papers citing "Exploiting compositionality to explore a large space of model structures"

30 / 30 papers shown

Title
Explaining the Success of Nearest Neighbor Methods in Prediction George H. Chen Devavrat Shah OOD 605 148 0 21 Feb 2025
Structure Learning via Mutual Information Jeremy Nixon 23 0 0 21 Sep 2024
G-EvoNAS: Evolutionary Neural Architecture Search Based on Network Growth Juan Zou Weiwei Jiang Yizhang Xia Yuan Liu Zhanglu Hou 94 0 0 05 Mar 2024
Gaussian Process Latent Variable Modeling for Few-shot Time Series Forecasting Yunyao Cheng Chenjuan Guo Kai Chen Kai Zhao B. Yang Jiandong Xie Christian S. Jensen Feiteng Huang Kai Zheng AI4TS 72 1 0 20 Dec 2022
Modelling Non-Smooth Signals with Complex Spectral Structure W. Bruinsma Martin Tegnér Richard Turner 79 6 0 14 Mar 2022
Bandits for Learning to Explain from Explanations Freya Behrens Stefano Teso Davide Mottin FAtt 41 1 0 07 Feb 2021
Learning Compositional Sparse Gaussian Processes with a Shrinkage Prior Anh Tong Toan M. Tran Hung Bui Jaesik Choi 37 3 0 21 Dec 2020
Automating Involutive MCMC using Probabilistic and Differentiable Programming Marco F. Cusumano-Towner Alexander K. Lew Vikash K. Mansinghka 76 17 0 20 Jul 2020
Dynamic Relational Inference in Multi-Agent Trajectories Ruichao Xiao Manish Kumar Singh Rose Yu 115 2 0 16 Jul 2020
A Survey of Machine Learning Methods and Challenges for Windows Malware Classification Edward Raff Charles K. Nicholas AAML 70 57 0 15 Jun 2020
Towards Assessing the Impact of Bayesian Optimization's Own Hyperparameters Marius Lindauer Matthias Feurer Katharina Eggensperger André Biedenkapp Frank Hutter 129 18 0 19 Aug 2019
Bayesian Synthesis of Probabilistic Programs for Automatic Data Modeling Feras A. Saad Marco F. Cusumano-Towner Ulrich Schaechtle Martin Rinard Vikash K. Mansinghka 58 62 0 14 Jul 2019
Modulating Surrogates for Bayesian Optimization Erik Bodin Markus Kaiser Ieva Kazlauskaite Zhenwen Dai Neill D. F. Campbell Carl Henrik Ek 30 2 0 26 Jun 2019
Neurally-Guided Structure Inference Sidi Lu Jiayuan Mao J. Tenenbaum Jiajun Wu 57 7 0 17 Jun 2019
Neural Architecture Optimization Renqian Luo Fei Tian Tao Qin Enhong Chen Tie-Yan Liu 3DV 112 659 0 22 Aug 2018
client2vec: Towards Systematic Baselines for Banking Applications Leonardo Baldassini Jose Antonio Rodríguez Serrano AI4TS 34 11 0 12 Feb 2018
Episodic memory for continual model learning D. G. Nagy Gergő Orbán CLL 21 0 0 04 Dec 2017
Progressive Neural Architecture Search Chenxi Liu Barret Zoph Maxim Neumann Jonathon Shlens Wei Hua Li Li Li Fei-Fei Alan Yuille Jonathan Huang Kevin Patrick Murphy 167 2,000 0 02 Dec 2017
Building machines that adapt and compute like brains Brenden M. Lake J. Tenenbaum AI4CE FedML NAI AILaw 331 887 0 11 Nov 2017
Meta-Learning MCMC Proposals Tongzhou Wang Yi Wu David A. Moore Stuart J. Russell BDL 80 2 0 21 Aug 2017
Hidden Physics Models: Machine Learning of Nonlinear Partial Differential Equations M. Raissi George Karniadakis AI4CE PINN 117 1,145 0 02 Aug 2017
Scaling up the Automatic Statistician: Scalable Structure Discovery using Gaussian Processes Hyunjik Kim Yee Whye Teh 77 52 0 08 Jun 2017
REMIX: Automated Exploration for Interactive Outlier Detection Yanjie Fu Charu C. Aggarwal Srinivasan Parthasarathy D. Turaga Hui Xiong 27 5 0 17 May 2017
Bachelor's thesis on generative probabilistic programming (in Russian language, June 2014) Yura N. Perov BDL 23 0 0 26 Jan 2016
Sandwiching the marginal likelihood using bidirectional Monte Carlo Roger C. Grosse Zoubin Ghahramani Ryan P. Adams 93 62 0 08 Nov 2015
A Latent Source Model for Online Collaborative Filtering Guy Bresler George H. Chen Devavrat Shah FedML 276 59 0 31 Oct 2014
Learning Probabilistic Programs Yura N. Perov Frank Wood TPM 73 15 0 09 Jul 2014
Venture: a higher-order probabilistic programming platform with programmable inference Vikash K. Mansinghka Daniel Selsam Yura N. Perov 106 256 0 01 Apr 2014
Automatic Construction and Natural-Language Description of Nonparametric Regression Models J. Lloyd David Duvenaud Roger C. Grosse J. Tenenbaum Zoubin Ghahramani 148 242 0 18 Feb 2014
Structure Discovery in Nonparametric Regression through Compositional Kernel Search David Duvenaud J. Lloyd Roger C. Grosse J. Tenenbaum Zoubin Ghahramani 121 511 0 20 Feb 2013