commit files to HF hub

papers.csv

@@ -704,7 +704,7 @@ Federated Heavy Hitter Recovery under Linear Sketching,"Adria Gascon, Peter Kair
 Optimal Stochastic Non-smooth Non-convex Optimization through Online-to-Non-convex Conversion,"Ashok Cutkosky, Harsh Mehta, Francesco Orabona",http://arxiv.org/abs/2302.03775,,https://huggingface.co/papers/2302.03775,,,,2302.03775,3,1
 Supervised Metric Learning to Rank for Retrieval via Contextual Similarity Optimization,"Christopher Liao, Theodoros Tsiligkaridis, Brian Kulis",http://arxiv.org/abs/2210.01908,https://github.com/Chris210634/metric-learning-using-contextual-similarity,https://huggingface.co/papers/2210.01908,,,,2210.01908,3,1
 User-defined Event Sampling and Uncertainty Quantification in Diffusion Models for Physical Dynamical Systems,"Marc Finzi, Anudhyan Boral, Leonardo Zepeda-Nunez, Andrew Wilson, Fei Sha",http://arxiv.org/abs/2306.07526,,https://huggingface.co/papers/2306.07526,,,,2306.07526,5,0
-Are Random Decompositions all we need in High Dimensional Bayesian Optimisation?,"Juliusz Ziomek, Haitham Bou Ammar",http://arxiv.org/abs/2301.12844,,https://huggingface.co/papers/2301.12844,,,,2301.12844,2,0
+Are Random Decompositions all we need in High Dimensional Bayesian Optimisation?,"Juliusz Ziomek, Haitham Bou Ammar",http://arxiv.org/abs/2301.12844,,https://huggingface.co/papers/2301.12844,,,,2301.12844,2,1
 Accelerated Primal-Dual Methods for Convex-Strongly-Concave Saddle Point Problems,"Mohammad Khalafi, Digvijay Boob",http://arxiv.org/abs/2209.04604,,https://huggingface.co/papers/2209.04604,,,,2209.04604,2,0
 "Extending Kernel PCA through Dualization: Sparsity, Robustness and Fast Algorithms","Francesco Tonin, Alex Lambert, Panagiotis Patrinos, Johan Suykens",http://arxiv.org/abs/2306.05815,,https://huggingface.co/papers/2306.05815,,,,2306.05815,4,0
 Improved Analysis of Score-based Generative Modeling: User-Friendly Bounds under Minimal Smoothness Assumptions,"Hongrui Chen, Holden Lee, Jianfeng Lu",http://arxiv.org/abs/2211.01916,,https://huggingface.co/papers/2211.01916,,,,2211.01916,3,1
@@ -714,7 +714,7 @@ On Preemption and Learning in Stochastic Scheduling,"Nadav Merlis, Hugo Richard,
 Joint Implicit Neural Representations for Global-Scale Species Mapping,"Elijah Cole, Grant Horn, Christian Lange, Alexander Shepard, Patrick Leary, Pietro Perona, Scott Loarie, Oisin Mac Aodha",,,,,,,,,
 TGRL: Teacher Guided Reinforcement Learning Algorithm,"Idan Shenfeld, Zhang-Wei Hong, Aviv Tamar, Pulkit Agrawal",,,,,,,,,
 Regions of Reliability in the Evaluation of Multivariate Probabilistic Forecasts,"Étienne Marcotte, Valentina Zantedeschi, Alexandre Drouin, Nicolas Chapados",http://arxiv.org/abs/2304.09836,,https://huggingface.co/papers/2304.09836,,,,2304.09836,4,0
-DualHSIC: HSIC-Bottleneck and Alignment for Continual Learning,"Zifeng Wang, Zheng Zhan, Yifan Gong, Yucai Shao, Stratis Ioannidis, Yanzhi Wang, Jennifer Dy",http://arxiv.org/abs/2305.00380,,https://huggingface.co/papers/2305.00380,,,,2305.00380,7,0
+DualHSIC: HSIC-Bottleneck and Alignment for Continual Learning,"Zifeng Wang, Zheng Zhan, Yifan Gong, Yucai Shao, Stratis Ioannidis, Yanzhi Wang, Jennifer Dy",http://arxiv.org/abs/2305.00380,,https://huggingface.co/papers/2305.00380,,,,2305.00380,7,1
 Mitigating Propagation Failures in Physics-informed Neural Networks using Retain-Resample-Release (R3) Sampling,"Arka Daw, Jie Bu, Sifan Wang, Paris Perdikaris, Anuj Karpatne",http://arxiv.org/abs/2207.02338,,https://huggingface.co/papers/2207.02338,,,,2207.02338,5,1
 Pareto Manifold Learning: Tackling multiple tasks via ensembles of single-task models,"Nikolaos Dimitriadis, Pascal Frossard, François Fleuret",http://arxiv.org/abs/2210.09759,,https://huggingface.co/papers/2210.09759,,,,2210.09759,3,1
 Approximate Stein Classes for Truncated Density Estimation,"Daniel J. Williams, Song Liu",http://arxiv.org/abs/2306.00602,,https://huggingface.co/papers/2306.00602,,,,2306.00602,2,1
@@ -1002,7 +1002,7 @@ Provably Learning Object-Centric Representations,"Jack Brady, Roland Zimmermann,
 Equivariant Architectures for Learning in Deep Weight Spaces,"Aviv Navon, Aviv Shamsian, Idan Achituve, Ethan Fetaya, Gal Chechik, Haggai Maron",http://arxiv.org/abs/2301.12780,,https://huggingface.co/papers/2301.12780,,,,2301.12780,6,1
 Difference of submodular minimization via DC programming,"Marwa El Halabi, George Orfanides, Tim Hoheisel",http://arxiv.org/abs/2305.11046,,https://huggingface.co/papers/2305.11046,,,,2305.11046,3,0
 Practical and Matching Gradient Variance Bounds for Black-Box Variational Bayesian Inference,"Kyurae Kim, Kaiwen Wu, Jisu Oh, Jacob Gardner",http://arxiv.org/abs/2303.10472,,https://huggingface.co/papers/2303.10472,,,,2303.10472,4,1
-Pre-training for Speech Translation: CTC Meets Optimal Transport,"Phuong-Hang Le, Hongyu Gong, Changhan Wang, Juan Pino, Benjamin Lecouteux, Didier Schwab",http://arxiv.org/abs/2301.11716,https://github.com/formiel/fairseq,https://huggingface.co/papers/2301.11716,,,,2301.11716,6,0
+Pre-training for Speech Translation: CTC Meets Optimal Transport,"Phuong-Hang Le, Hongyu Gong, Changhan Wang, Juan Pino, Benjamin Lecouteux, Didier Schwab",http://arxiv.org/abs/2301.11716,https://github.com/formiel/fairseq,https://huggingface.co/papers/2301.11716,,,,2301.11716,6,1
 StyleGAN-T: Unlocking the Power of GANs for Fast Large-Scale Text-to-Image Synthesis,"Axel Sauer, Axel Sauer, Tero Karras, Samuli Laine, Andreas Geiger, Timo Aila",,,,,,,,,
 BEATs: Audio Pre-Training with Acoustic Tokenizers,"Sanyuan Chen, Yu Wu, Chengyi Wang, Shujie Liu, Daniel Tompkins, Zhuo Chen, Wanxiang Che, Xiangzhan Yu, Furu Wei",http://arxiv.org/abs/2212.09058,,https://huggingface.co/papers/2212.09058,,,,2212.09058,7,0
 "Efficient Self-supervised Learning with Contextualized Target Representations for Vision, Speech and Language","Alexei Baevski, Arun Babu, Wei-Ning Hsu, Michael Auli",http://arxiv.org/abs/2212.07525,,https://huggingface.co/papers/2212.07525,,,,2212.07525,4,1