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检索条件"机构=Google and Yale Institute for Foundations of Data Science"
28 条 记 录,以下是1-10 订阅
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Approximation of relation functions and attention mechanisms
arXiv
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arXiv 2024年
作者: Altabaa, Awni Lafferty, John Department of Statistics and Data Science Yale University United States Department of Statistics and Data Science Wu Tsai Institute Institute for Foundations of Data Science Yale University United States
Inner products of neural network feature maps arise in a wide variety of machine learning frameworks as a method of modeling relations between inputs. This work studies the approximation properties of inner products o... 详细信息
来源: 评论
TRANSFER LEARNING BEYOND BOUNDED DENSITY RATIOS
arXiv
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arXiv 2024年
作者: Kalavasis, Alkis Zadik, Ilias Zampetakis, Manolis Department of Statistics and Data Science Yale University United States Department of Computer Science Yale University United States Institute of Foundations of Data Science Yale University United States
We study the fundamental problem of transfer learning where a learning algorithm collects data from some source distribution P but needs to perform well with respect to a different target distribution Q. A standard ch... 详细信息
来源: 评论
Cell2Sentence: Teaching Large Language Models the Language of Biology  41
Cell2Sentence: Teaching Large Language Models the Language o...
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41st International Conference on Machine Learning, ICML 2024
作者: Levine, Daniel Rizvi, Syed Asad Lévy, Sacha Pallikkavaliyaveetil, Nazreen Zhang, David Chen, Xingyu Ghadermarzi, Sina Wu, Ruiming Zheng, Zihe Vrkic, Ivan Zhong, Anna Raskin, Daphne Han, Insu de Oliveira Fonseca, Antonio Henrique Caro, Josue Ortega Karbasi, Amin Dhodapkar, Rahul M. van Dijk, David Department of Computer Science Yale University New HavenCT United States School of Engineering Applied Science University of Pennsylvania PhiladelphiaPA United States School of Computer and Communication Sciences Swiss Federal Institute of Technology Lausanne Lausanne Switzerland Department of Neuroscience Yale School of Medicine New HavenCT United States Wu Tsai Institute Yale University New HavenCT United States Google United States Yale Institute for Foundations of Data Science New HavenCT United States Yale School of Engineering and Applied Science New HavenCT United States Roski Eye Institute University of Southern California Los AngelesCA United States Yale School of Medicine New HavenCT United States Cardiovascular Research Center Yale School of Medicine New HavenCT United States Interdepartmental Program in Computational Biology & Bioinformatics Yale University New HavenCT United States
We introduce Cell2Sentence (C2S), a novel method to directly adapt large language models to a biological context, specifically single-cell transcriptomics. By transforming gene expression data into"cell sentences... 详细信息
来源: 评论
From task structures to world models: What do LLMs know?
arXiv
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arXiv 2023年
作者: Yildirim, Ilker Paul, L.A. Department of Psychology Yale University United States Department of Philosophy Yale University United States Department of Statistics & Data Science Yale University United States Wu-Tsai Institute Yale University United States Foundations of the Data Science Institute Yale University United States
In what sense does a large language model have knowledge? The answer to this question extends beyond the capabilities of a particular AI system, and challenges our assumptions about the nature of knowledge and intelli...
来源: 评论
Cell2Sentence: teaching large language models the language of biology  24
Cell2Sentence: teaching large language models the language o...
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Proceedings of the 41st International Conference on Machine Learning
作者: Daniel Levine Syed Asad Rizvi Sacha Lévy Nazreen Pallikkavaliyaveetil David Zhang Xingyu Chen Sina Ghadermarzi Ruiming Wu Zihe Zheng Ivan Vrkic Anna Zhong Daphne Raskin Insu Han Antonio Henrique De Oliveira Fonseca Josue Ortega Caro Amin Karbasi Rahul M. Dhodapkar David Van Dijk Department of Computer Science Yale University New Haven CT School of Engineering Applied Science University of Pennsylvania Philadelphia PA School of Computer and Communication Sciences Swiss Federal Institute of Technology Lausanne Lausanne Switzerland Department of Computer Science Yale University New Haven CT and Department of Neuroscience Yale School of Medicine New Haven CT Department of Computer Science Yale University New Haven CT and Department of Neuroscience Yale School of Medicine New Haven CT and Wu Tsai Institute Yale University New Haven CT Google and Yale Institute for Foundations of Data Science New Haven CT and Department of Computer Science Yale University New Haven CT and Yale School of Engineering and Applied Science New Haven CT Roski Eye Institute University of Southern California Los Angeles CA and Department of Internal Medicine (Cardiology) Yale School of Medicine New Haven CT Department of Computer Science Yale University New Haven CT and Yale Institute for Foundations of Data Science New Haven CT and Wu Tsai Institute Yale University New Haven CT and Cardiovascular Research Center Yale School of Medicine New Haven CT and Interdepartmental Program in Computational Biology & Bioinformatics Yale University New Haven CT and Department of Internal Medicine (Cardiology) Yale School of Medicine New Haven CT
We introduce Cell2Sentence (C2S), a novel method to directly adapt large language models to a biological context, specifically single-cell transcriptomics. By transforming gene expression data into "cell sentence...
来源: 评论
MambaLRP: Explaining Selective State Space Sequence Models  38
MambaLRP: Explaining Selective State Space Sequence Models
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38th Conference on Neural Information Processing Systems, NeurIPS 2024
作者: Jafari, Farnoush Rezaei Montavon, Grégoire Müller, Klaus-Robert Eberle, Oliver Machine Learning Group Technische Universität Berlin Berlin10587 Germany BIFOLD - Berlin Institute for the Foundations of Learning and Data Berlin10587 Germany Department of Mathematics and Computer Science Freie Universität Berlin Arnimallee 14 Berlin14195 Germany Department of Artificial Intelligence Korea University Seoul136-713 Korea Republic of Max Planck Institute for Informatics Stuhlsatzenhausweg 4 Saarbrücken66123 Germany Google DeepMind Berlin Germany
Recent sequence modeling approaches using selective state space sequence models, referred to as Mamba models, have seen a surge of interest. These models allow efficient processing of long sequences in linear time and...
来源: 评论
Improved classical shadows from local symmetries in the Schur basis
arXiv
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arXiv 2024年
作者: Grier, Daniel Liu, Sihan Mahajan, Gaurav Department of Computer Science and Engineering Department of Mathematics UC San Diego United States Department of Computer Science and Engineering UCSD California CA92092 United States Institute for Foundations of Data Science Yale University Connecticut CT06511 United States
We study the sample complexity of the classical shadows task: what is the fewest number of copies of an unknown state you need to measure to predict expected values with respect to some class of observables? Large joi...
来源: 评论
MambaLRP: explaining selective state space sequence models  24
MambaLRP: explaining selective state space sequence models
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Proceedings of the 38th International Conference on Neural Information Processing Systems
作者: Farnoush Rezaei Jafari Grégoire Montavon Klaus-Robert Müller Oliver Eberle Machine Learning Group Technische Universität Berlin Berlin Germany and BIFOLD - Berlin Institute for the Foundations of Learning and Data Berlin Germany Department of Mathematics and Computer Science Freie Universitat Berlin Berlin Germany and BIFOLD - Berlin Institute for the Foundations of Learning and Data Berlin Germany and Machine Learning Group Technische Universität Berlin Berlin Germany BIFOLD - Berlin Institute for the Foundations of Learning and Data Berlin Germany and Machine Learning Group Technische Universität Berlin Berlin Germany and Department of Artificial Intelligence Korea University Seoul South Korea and Max Planck Institute for Informatics Saarbrücken Germany and Google DeepMind Berlin Germany
Recent sequence modeling approaches using selective state space sequence models, referred to as Mamba models, have seen a surge of interest. These models allow efficient processing of long sequences in linear time and...
来源: 评论
Analyzing Atomic Interactions in Molecules as Learned by Neural Networks
arXiv
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arXiv 2024年
作者: Esders, Malte Schnake, Thomas Lederer, Jonas Kabylda, Adil Montavon, Grégoire Tkatchenko, Alexandre Müller, Klaus-Robert BIFOLD Berlin Institute for the Foundations of Learning and Data Germany Machine Learning Group Berlin Institute of Technology Berlin10587 Germany Department of Physics and Materials Science University of Luxembourg Luxembourg CityL-1511 Luxembourg Department of Mathematics and Computer Science Free University of Berlin Germany Google Deepmind Berlin Germany Department of Artificial Intelligence Korea University Seoul136-713 Korea Republic of Max Planck Institute for Informatics Saarbrücken66123 Germany
While machine learning (ML) models have been able to achieve unprecedented accuracies across various prediction tasks in quantum chemistry, it is now apparent that accuracy on a test set alone is not a guarantee for r... 详细信息
来源: 评论
The Clever Hans Effect in Unsupervised Learning
arXiv
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arXiv 2024年
作者: Kauffmann, Jacob Dippel, Jonas Ruff, Lukas Samek, Wojciech Müller, Klaus-Robert Montavon, Grégoire Department of Electrical Engineering and Computer Science Technische Universität Berlin Germany BIFOLD – Berlin Institute for the Foundations of Learning and Data Berlin Germany Aignostics Berlin Germany Department of Mathematics and Computer Science Freie Universität Berlin Germany Department of Artificial Intelligence Fraunhofer HHI Berlin Germany Department of Artificial Intelligence Korea University Seoul Korea Republic of Max-Planck Institute for Informatics Saarbrücken Germany Google Deepmind Berlin Germany
Unsupervised learning has become an essential building block of AI systems. The representations it produces, e.g. in foundation models, are critical to a wide variety of downstream applications. It is therefore import... 详细信息
来源: 评论