Papers
11,015 papers found
Constraining Representations Yields Models That Know What They Don't Know
Joao Monteiro, Pau Rodriguez, Pierre-Andre Noel et al.
Constructive TT-representation of the tensors given as index interaction functions with applications
Gleb Ryzhakov, Ivan Oseledets
Context-enriched molecule representations improve few-shot drug discovery
Johannes Schimunek, Philipp Seidl, Lukas Friedrich et al.
Contextual bandits with concave rewards, and an application to fair ranking
Virginie Do, Elvis Dohmatob, Matteo Pirotta et al.
Contextual Convolutional Networks
Shuxian Liang, Xu Shen, Tongliang Liu et al.
Contextual Image Masking Modeling via Synergized Contrasting without View Augmentation for Faster and Better Visual Pretraining
Shaofeng Zhang, Feng Zhu, Rui Zhao et al.
Continual evaluation for lifelong learning: Identifying the stability gap
Matthias De Lange, Gido M van de Ven, Tinne Tuytelaars
Continual Pre-training of Language Models
Zixuan Ke, Yijia Shao, Haowei Lin et al.
Continual Transformers: Redundancy-Free Attention for Online Inference
Lukas Hedegaard, Arian Bakhtiarnia, Alexandros Iosifidis
Continual Unsupervised Disentangling of Self-Organizing Representations
Zhiyuan Li, Xiajun Jiang, Ryan Missel et al.
Continuized Acceleration for Quasar Convex Functions in Non-Convex Optimization
Jun-Kun Wang, Andre Wibisono
Continuous-Discrete Convolution for Geometry-Sequence Modeling in Proteins
Hehe Fan, Zhangyang Wang, Yi Yang et al.
Continuous PDE Dynamics Forecasting with Implicit Neural Representations
Yuan Yin, Matthieu Kirchmeyer, Jean-Yves Franceschi et al.
Continuous pseudo-labeling from the start
Dan Berrebbi, Ronan Collobert, Samy Bengio et al.
Continuous-time identification of dynamic state-space models by deep subspace encoding
Gerben I. Beintema, Maarten Schoukens, Roland Tóth
ContraNorm: A Contrastive Learning Perspective on Oversmoothing and Beyond
Xiaojun Guo, Yifei Wang, Tianqi Du et al.
Contrastive Audio-Visual Masked Autoencoder
Yuan Gong, Andrew Rouditchenko, Alexander H. Liu et al.
Contrastive Corpus Attribution for Explaining Representations
Chris Lin, Hugh Chen, Chanwoo Kim et al.
Contrastive Learning Can Find An Optimal Basis For Approximately View-Invariant Functions
Daniel D. Johnson, Ayoub El Hanchi, Chris J. Maddison
Contrastive Learning for Unsupervised Domain Adaptation of Time Series
Yilmazcan Ozyurt, Stefan Feuerriegel, Ce Zhang
Contrastive Meta-Learning for Partially Observable Few-Shot Learning
Adam Jelley, Amos Storkey, Antreas Antoniou et al.
Copy is All You Need
Tian Lan, Deng Cai, Yan Wang et al.
Correlative Information Maximization Based Biologically Plausible Neural Networks for Correlated Source Separation
Bariscan Bozkurt, Ateş İsfendiyaroğlu, Cengiz Pehlevan et al.
Corrupted Image Modeling for Self-Supervised Visual Pre-Training
Yuxin Fang, Li Dong, Hangbo Bao et al.