Papers
On the non-universality of deep learning: quantifying the cost of symmetry
Emmanuel Abbe, Enric Boix-Adsera
On the Parameterization and Initialization of Diagonal State Space Models
Albert Gu, Karan Goel, Ankit Gupta et al.
On the relationship between variational inference and auto-associative memory
Louis Annabi, Alexandre Pitti, Mathias Quoy
On the Representation Collapse of Sparse Mixture of Experts
Zewen Chi, Li Dong, Shaohan Huang et al.
On the Robustness of Deep Clustering Models: Adversarial Attacks and Defenses
Anshuman Chhabra, Ashwin Sekhari, Prasant Mohapatra
On the Robustness of Graph Neural Diffusion to Topology Perturbations
Yang Song, Qiyu Kang, Sijie Wang et al.
On the Safety of Interpretable Machine Learning: A Maximum Deviation Approach
Dennis Wei, Rahul Nair, Amit Dhurandhar et al.
On the Sample Complexity of Stabilizing LTI Systems on a Single Trajectory
Yang Hu, Adam Wierman, Guannan Qu
On the SDEs and Scaling Rules for Adaptive Gradient Algorithms
Sadhika Malladi, Kaifeng Lyu, Abhishek Panigrahi et al.
On the Spectral Bias of Convolutional Neural Tangent and Gaussian Process Kernels
Amnon Geifman, Meirav Galun, David Jacobs et al.
On the Stability and Scalability of Node Perturbation Learning
Naoki Hiratani, Yash Mehta, Timothy Lillicrap et al.
On the Statistical Efficiency of Reward-Free Exploration in Non-Linear RL
Jinglin Chen, Aditya Modi, Akshay Krishnamurthy et al.
On the Strong Correlation Between Model Invariance and Generalization
Weijian Deng, Stephen Gould, Liang Zheng
On the Symmetries of Deep Learning Models and their Internal Representations
Charles Godfrey, Davis Brown, Tegan Emerson et al.
On the symmetries of the synchronization problem in Cryo-EM: Multi-Frequency Vector Diffusion Maps on the Projective Plane
Gabriele Cesa, Arash Behboodi, Taco S Cohen et al.
On the Theoretical Properties of Noise Correlation in Stochastic Optimization
Aurelien Lucchi, Frank Proske, Antonio Orvieto et al.
On the Tradeoff Between Robustness and Fairness
Xinsong Ma, Zekai Wang, Weiwei Liu
Ontologue: Declarative Benchmark Construction for Ontological Multi-Label Classification
Sean Yang, Bernease Herman, Bill Howe
On Translation and Reconstruction Guarantees of the Cycle-Consistent Generative Adversarial Networks
Anish Chakrabarty, Swagatam Das
On Uncertainty, Tempering, and Data Augmentation in Bayesian Classification
Sanyam Kapoor, Wesley J Maddox, Pavel Izmailov et al.
OOD Link Prediction Generalization Capabilities of Message-Passing GNNs in Larger Test Graphs
Yangze Zhou, Gitta Kutyniok, Bruno Ribeiro
OpenAUC: Towards AUC-Oriented Open-Set Recognition
Zitai Wang, Qianqian Xu, Zhiyong Yang et al.
Open-Ended Reinforcement Learning with Neural Reward Functions
Robert Meier, Asier Mujika
OpenFilter: A Framework to Democratize Research Access to Social Media AR Filters
Piera Riccio, Bill Psomas, Francesco Galati et al.