On the Promise for Assurance of Differentiable Neurosymbolic Reasoning Paradigms

13 February 2025

Papers citing "On the Promise for Assurance of Differentiable Neurosymbolic Reasoning Paradigms"

28 / 28 papers shown

Title
Remote Timing Attacks on Efficient Language Model Inference Nicholas Carlini Milad Nasr 47 3 0 22 Oct 2024
Data-Efficient Learning with Neural Programs Alaia Solko-Breslin Seewon Choi Ziyang Li Neelay Velingker Rajeev Alur Mayur Naik Eric Wong 58 6 0 10 Jun 2024
Not All Neuro-Symbolic Concepts Are Created Equal: Analysis and Mitigation of Reasoning Shortcuts Emanuele Marconato Stefano Teso Antonio Vergari Andrea Passerini 78 35 0 31 May 2023
Do Machine Learning Models Learn Statistical Rules Inferred from Data? Aaditya Naik Yinjun Wu Mayur Naik Eric Wong 34 4 0 02 Mar 2023
Part-Based Models Improve Adversarial Robustness Chawin Sitawarin Kornrapat Pongmala Yizheng Chen Nicholas Carlini David Wagner 63 12 0 15 Sep 2022
Safe Neurosymbolic Learning with Differentiable Symbolic Execution Chenxi Yang Swarat Chaudhuri 43 9 0 15 Mar 2022
A Survey on AI Assurance Feras A. Batarseh Laura J. Freeman 63 66 0 15 Nov 2021
Neuro-Symbolic Artificial Intelligence: Current Trends Md Kamruzzaman Sarker Lu Zhou Aaron Eberhart Pascal Hitzler NAI 46 92 0 11 May 2021
Fairness in Machine Learning L. Oneto Silvia Chiappa FaML 282 494 0 31 Dec 2020
Long Range Arena: A Benchmark for Efficient Transformers Yi Tay Mostafa Dehghani Samira Abnar Songlin Yang Dara Bahri Philip Pham J. Rao Liu Yang Sebastian Ruder Donald Metzler 136 718 0 08 Nov 2020
Measuring Robustness to Natural Distribution Shifts in Image Classification Rohan Taori Achal Dave Vaishaal Shankar Nicholas Carlini Benjamin Recht Ludwig Schmidt OOD 108 546 0 01 Jul 2020
How fair can we go in machine learning? Assessing the boundaries of fairness in decision trees Ana Valdivia Javier Sánchez-Monedero J. Casillas FaML 52 46 0 22 Jun 2020
wav2vec 2.0: A Framework for Self-Supervised Learning of Speech Representations Alexei Baevski Henry Zhou Abdel-rahman Mohamed Michael Auli SSL 252 5,774 0 20 Jun 2020
Certified Robustness to Label-Flipping Attacks via Randomized Smoothing Elan Rosenfeld Ezra Winston Pradeep Ravikumar J. Zico Kolter OOD AAML 59 156 0 07 Feb 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 408 42,393 0 03 Dec 2019
Neural Probabilistic Logic Programming in DeepProbLog Robin Manhaeve Sebastijan Dumancic Angelika Kimmig T. Demeester Luc de Raedt NAI 80 555 0 18 Jul 2019
Benchmarking Robustness in Object Detection: Autonomous Driving when Winter is Coming Claudio Michaelis Benjamin Mitzkus Robert Geirhos E. Rusak Oliver Bringmann Alexander S. Ecker Matthias Bethge Wieland Brendel 3DPC 95 444 0 17 Jul 2019
MNIST-C: A Robustness Benchmark for Computer Vision Norman Mu Justin Gilmer 52 210 0 05 Jun 2019
Benchmarking Neural Network Robustness to Common Corruptions and Perturbations Dan Hendrycks Thomas G. Dietterich OOD VLM 167 3,429 0 28 Mar 2019
advertorch v0.1: An Adversarial Robustness Toolbox based on PyTorch G. Ding Luyu Wang Xiaomeng Jin 63 183 0 20 Feb 2019
Certified Adversarial Robustness via Randomized Smoothing Jeremy M. Cohen Elan Rosenfeld J. Zico Kolter AAML 130 2,036 0 08 Feb 2019
An Empirical Study of Rich Subgroup Fairness for Machine Learning Michael Kearns Seth Neel Aaron Roth Zhiwei Steven Wu FaML 95 206 0 24 Aug 2018
On Calibration of Modern Neural Networks Chuan Guo Geoff Pleiss Yu Sun Kilian Q. Weinberger UQCV 291 5,825 0 14 Jun 2017
Fairness Beyond Disparate Treatment & Disparate Impact: Learning Classification without Disparate Mistreatment Muhammad Bilal Zafar Isabel Valera Manuel Gomez Rodriguez Krishna P. Gummadi FaML 190 1,205 0 26 Oct 2016
Very Deep Convolutional Neural Networks for Raw Waveforms Wei Dai Chia Dai Shuhui Qu Juncheng Billy Li Samarjit Das 105 345 0 01 Oct 2016
Deep Residual Learning for Image Recognition Kaiming He Xinming Zhang Shaoqing Ren Jian Sun MedIm 2.2K 193,814 0 10 Dec 2015
The Limitations of Deep Learning in Adversarial Settings Nicolas Papernot Patrick McDaniel S. Jha Matt Fredrikson Z. Berkay Celik A. Swami AAML 98 3,957 0 24 Nov 2015
Towards Deep Neural Network Architectures Robust to Adversarial Examples S. Gu Luca Rigazio AAML 76 841 0 11 Dec 2014