Neural Networks for Partially Linear Quantile Regression

11 June 2021

Papers citing "Neural Networks for Partially Linear Quantile Regression"

34 / 34 papers shown

Title
Neural Bayes Estimators for Irregular Spatial Data using Graph Neural Networks Matthew Sainsbury-Dale A. Zammit‐Mangion J. Richards Raphael Huser 637 15 0 04 Oct 2023
Deep Quantile Regression: Mitigating the Curse of Dimensionality Through Composition Guohao Shen Yuling Jiao Yuanyuan Lin J. Horowitz Jian Huang 241 23 0 10 Jul 2021
Significance tests of feature relevance for a black-box learner Ben Dai Xiaotong Shen Wei Pan 149 27 0 02 Mar 2021
Quantile regression with deep ReLU Networks: Estimators and minimax rates Oscar Hernan Madrid Padilla Wesley Tansey Yanzhen Chen 275 29 0 16 Oct 2020
Quantile Regression Neural Networks: A Bayesian Approach Sanket Jantre Shrijita Bhattacharya T. Maiti 110 11 0 28 Sep 2020
PyTorch: An Imperative Style, High-Performance Deep Learning Library Adam Paszke Sam Gross Francisco Massa Adam Lerer James Bradbury ... Sasank Chilamkurthy Benoit Steiner Lu Fang Junjie Bai Soumith Chintala ODL 547 42,591 0 03 Dec 2019
On Completeness-aware Concept-Based Explanations in Deep Neural Networks Chih-Kuan Yeh Been Kim Sercan O. Arik Chun-Liang Li Tomas Pfister Pradeep Ravikumar FAtt 263 307 0 17 Oct 2019
Adapting Neural Networks for the Estimation of Treatment Effects Claudia Shi David M. Blei Victor Veitch CML 148 376 0 05 Jun 2019
Conformalized Quantile Regression Yaniv Romano Evan Patterson Emmanuel J. Candès 491 616 0 08 May 2019
A Selective Overview of Deep Learning Jianqing Fan Cong Ma Yiqiao Zhong BDL VLM 172 135 0 10 Apr 2019
Interpretable machine learning: definitions, methods, and applications W. James Murdoch Chandan Singh Karl Kumbier R. Abbasi-Asl Bin Yu XAI HAI 201 1,444 0 14 Jan 2019
Deep Neural Networks for Estimation and Inference M. Farrell Tengyuan Liang S. Misra BDL 176 255 0 26 Sep 2018
This Looks Like That: Deep Learning for Interpretable Image Recognition Chaofan Chen Oscar Li Chaofan Tao A. Barnett Jonathan Su Cynthia Rudin 250 1,188 0 27 Jun 2018
Interpretability Beyond Feature Attribution: Quantitative Testing with Concept Activation Vectors (TCAV) Been Kim Martin Wattenberg Justin Gilmer Carrie J. Cai James Wexler F. Viégas Rory Sayres FAtt 232 1,850 0 30 Nov 2017
Deep Learning for Case-Based Reasoning through Prototypes: A Neural Network that Explains Its Predictions Oscar Li Hao Liu Chaofan Chen Cynthia Rudin 178 593 0 13 Oct 2017
Smooth Pinball Neural Network for Probabilistic Forecasting of Wind Power Kostas Hatalis A. Lamadrid K. Scheinberg S. Kishore 130 21 0 04 Oct 2017
Optimal approximation of piecewise smooth functions using deep ReLU neural networks P. Petersen Felix Voigtländer 223 475 0 15 Sep 2017
Nonparametric regression using deep neural networks with ReLU activation function Johannes Schmidt-Hieber 238 815 0 22 Aug 2017
The power of deeper networks for expressing natural functions David Rolnick Max Tegmark 158 174 0 16 May 2017
Double/Debiased/Neyman Machine Learning of Treatment Effects Victor Chernozhukov Denis Chetverikov Mert Demirer E. Duflo Christian B. Hansen Whitney Newey CML FedML 149 351 0 30 Jan 2017
Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization Ramprasaath R. Selvaraju Michael Cogswell Abhishek Das Ramakrishna Vedantam Devi Parikh Dhruv Batra FAtt 325 20,086 0 07 Oct 2016
Error bounds for approximations with deep ReLU networks Dmitry Yarotsky 198 1,233 0 03 Oct 2016
Quantile Processes for Semi and Nonparametric Regression Shih-Kang Chao S. Volgushev Guang Cheng 297 25 0 07 Apr 2016
Benefits of depth in neural networks Matus Telgarsky 378 609 0 14 Feb 2016
Partially linear additive quantile regression in ultra-high dimension Ben Sherwood Lan Wang 152 111 0 22 Jan 2016
Learning both Weights and Connections for Efficient Neural Networks Song Han Jeff Pool J. Tran W. Dally CVBM 316 6,700 0 08 Jun 2015
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 2.1K 150,364 0 22 Dec 2014
ImageNet Large Scale Visual Recognition Challenge Olga Russakovsky Jia Deng Hao Su J. Krause S. Satheesh ... A. Karpathy A. Khosla Michael S. Bernstein Alexander C. Berg Li Fei-Fei VLM ObjD 1.7K 39,595 0 01 Sep 2014
Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps Karen Simonyan Andrea Vedaldi Andrew Zisserman FAtt 314 7,317 0 20 Dec 2013
Visualizing and Understanding Convolutional Networks Matthew D. Zeiler Rob Fergus FAtt SSL 595 15,904 0 12 Nov 2013
Conditional Quantile Processes based on Series or Many Regressors A. Belloni Victor Chernozhukov Denis Chetverikov Iván Fernández�?Val 157 42 0 31 May 2011
Uniform bias study and Bahadur representation for local polynomial estimators of the conditional quantile function E. Guerre Camille Sabbah 214 80 0 25 May 2011
Natural Language Processing (almost) from Scratch R. Collobert Jason Weston Léon Bottou Michael Karlen Koray Kavukcuoglu Pavel P. Kuksa 203 7,728 0 02 Mar 2011
Quantile regression in partially linear varying coefficient models H. Wang Zhongyi Zhu Jianhui Zhou 227 269 0 18 Nov 2009