Papers
Neural networks grown and self-organized by noise
Guruprasad Raghavan, Matt Thomson
Cascaded Dilated Dense Network with Two-step Data Consistency for MRI Reconstruction
Hao Zheng, Faming Fang, Guixu Zhang
Graph Normalizing Flows
Jenny Liu, Aviral Kumar, Jimmy Ba 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.
Reducing the variance in online optimization by transporting past gradients
Sébastien Arnold, Pierre-Antoine Manzagol, Reza Babanezhad Harikandeh et al.
Fast Convergence of Natural Gradient Descent for Over-Parameterized Neural Networks
Guodong Zhang, James Martens, Roger B Grosse
Exploring Algorithmic Fairness in Robust Graph Covering Problems
Aida Rahmattalabi, Phebe Vayanos, Anthony Fulginiti et al.
Controllable Text-to-Image Generation
Bowen Li, Xiaojuan Qi, Thomas Lukasiewicz et al.
ADDIS: an adaptive discarding algorithm for online FDR control with conservative nulls
Jinjin Tian, Aaditya Ramdas
On two ways to use determinantal point processes for Monte Carlo integration
Guillaume Gautier, Rémi Bardenet, Michal Valko
Attentive State-Space Modeling of Disease Progression
Ahmed M. Alaa, Mihaela van der Schaar
Invariance-inducing regularization using worst-case transformations suffices to boost accuracy and spatial robustness
Fanny Yang, Zuowen Wang, Christina Heinze-Deml
Learning to Confuse: Generating Training Time Adversarial Data with Auto-Encoder
Ji Feng, Qi-Zhi Cai, Zhi-Hua Zhou
Preventing Gradient Attenuation in Lipschitz Constrained Convolutional Networks
Qiyang Li, Saminul Haque, Cem Anil et al.
MixMatch: A Holistic Approach to Semi-Supervised Learning
David Berthelot, Nicholas Carlini, Ian Goodfellow et al.
Globally Optimal Learning for Structured Elliptical Losses
Yoav Wald, Nofar Noy, Gal Elidan et al.
Accurate Uncertainty Estimation and Decomposition in Ensemble Learning
Jeremiah Liu, John Paisley, Marianthi-Anna Kioumourtzoglou et al.
Joint Optimization of Tree-based Index and Deep Model for Recommender Systems
Han Zhu, Daqing Chang, Ziru Xu et al.
Calibration tests in multi-class classification: A unifying framework
David Widmann, Fredrik Lindsten, Dave Zachariah
Push-pull Feedback Implements Hierarchical Information Retrieval Efficiently
Xiao Liu, Xiaolong Zou, Zilong Ji et al.
Correlation Priors for Reinforcement Learning
Bastian Alt, Adrian Šošić, Heinz Koeppl
MonoForest framework for tree ensemble analysis
Igor Kuralenok, Vasilii Ershov, Igor Labutin
Ouroboros: On Accelerating Training of Transformer-Based Language Models
Qian Yang, Zhouyuan Huo, Wenlin Wang et al.
When to use parametric models in reinforcement learning?
Hado P van Hasselt, Matteo Hessel, John Aslanides
On the Fairness of Disentangled Representations
Francesco Locatello, Gabriele Abbati, Thomas Rainforth et al.