Papers
Deep Model Transferability from Attribution Maps
Jie Song, Yixin Chen, Xinchao Wang et al.
Deep Multimodal Multilinear Fusion with High-order Polynomial Pooling
Ming Hou, Jiajia Tang, Jianhai Zhang et al.
Deep Multi-State Dynamic Recurrent Neural Networks Operating on Wavelet Based Neural Features for Robust Brain Machine Interfaces
Benyamin Allahgholizadeh Haghi, Spencer Kellis, Sahil Shah et al.
Deep Random Splines for Point Process Intensity Estimation of Neural Population Data
Gabriel Loaiza-Ganem, Sean Perkins, Karen Schroeder et al.
Deep ReLU Networks Have Surprisingly Few Activation Patterns
Boris Hanin, David Rolnick
Deep RGB-D Canonical Correlation Analysis For Sparse Depth Completion
Yiqi Zhong, Cho-Ying Wu, Suya You et al.
Deep Scale-spaces: Equivariance Over Scale
Daniel Worrall, Max Welling
Deep Set Prediction Networks
Yan Zhang, Jonathon Hare, Adam Prugel-Bennett
Deep Signature Transforms
Patrick Kidger, Patric Bonnier, Imanol Perez Arribas et al.
Deep Structured Prediction for Facial Landmark Detection
Lisha Chen, Hui Su, Qiang Ji
Deep Supervised Summarization: Algorithm and Application to Learning Instructions
Chengguang Xu, Ehsan Elhamifar
DeepUSPS: Deep Robust Unsupervised Saliency Prediction via Self-supervision
Tam Nguyen, Maximilian Dax, Chaithanya Kumar Mummadi et al.
DeepWave: A Recurrent Neural-Network for Real-Time Acoustic Imaging
Matthieu SIMEONI, Sepand Kashani, Paul Hurley et al.
Defending Against Neural Fake News
Rowan Zellers, Ari Holtzman, Hannah Rashkin et al.
Defending Neural Backdoors via Generative Distribution Modeling
Ximing Qiao, Yukun Yang, Hai Li
Defense Against Adversarial Attacks Using Feature Scattering-based Adversarial Training
Haichao Zhang, Jianyu Wang
Deliberative Explanations: visualizing network insecurities
Pei Wang, Nuno Nvasconcelos
Demystifying Black-box Models with Symbolic Metamodels
Ahmed M. Alaa, Mihaela van der Schaar
Depth-First Proof-Number Search with Heuristic Edge Cost and Application to Chemical Synthesis Planning
Akihiro Kishimoto, Beat Buesser, Bei Chen et al.
Detecting Overfitting via Adversarial Examples
Roman Werpachowski, András György, Csaba Szepesvari
DetNAS: Backbone Search for Object Detection
Yukang Chen, Tong Yang, Xiangyu Zhang et al.
DETOX: A Redundancy-based Framework for Faster and More Robust Gradient Aggregation
Shashank Rajput, Hongyi Wang, Zachary Charles et al.
Devign: Effective Vulnerability Identification by Learning Comprehensive Program Semantics via Graph Neural Networks
Yaqin Zhou, Shangqing Liu, Jingkai Siow et al.
DFNets: Spectral CNNs for Graphs with Feedback-Looped Filters
W. O. K. Asiri Suranga Wijesinghe, Qing Wang
Dichotomize and Generalize: PAC-Bayesian Binary Activated Deep Neural Networks
Gaël Letarte, Pascal Germain, Benjamin Guedj et al.