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Generative AI has redefined artificial intelligence, enabling the creation of innovative content and customized solutions that drive business practices into a new era of efficiency and creativity.
A global geometric framework for nonlinear dimensionality reduction
Joshua B Tenenbaum, Vin de Silva, and John C Langford · 2000
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A distribution-free theory of nonparametric regression , volume 1
László Györfi, Michael Köhler, Adam Krzyżak, and Harro Walk · 2002
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Estimation of non-normalized statistical models by score matching
Aapo Hyvärinen and Peter Dayan · 2005
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Reinforcement learning by reward-weighted regression for operational space control
Jan Peters and Stefan Schaal · 2007
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Finite-time bounds for fitted value iteration
Rémi Munos and Csaba Szepesvári · 2008
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Introduction to Nonparametric Estimation
Alexandre B. Tsybakov · 2008
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Imagenet: A large-scale hierarchical image database
Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei · 2009
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Learning multiple layers of features from tiny images
Alex Krizhevsky, Geoffrey Hinton, et al · 2009
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Dynamic discrete choice structural models: A survey
Victor Aguirregabiria and Pedro Mira · 2010
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Improved algorithms for linear stochastic bandits
Yasin Abbasi-Yadkori, Dávid Pál, and Csaba Szepesvári · 2011
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A tail inequality for quadratic forms of subgaussian random vectors, 2011
Daniel Hsu, Sham M. Kakade, and Tong Zhang · 2011
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Score-based generative modeling through stochastic differential equations
Yang Song, Jascha Sohl-Dickstein, Diederik P Kingma, Abhishek Kumar, Stefano Ermon, and Ben Poole · 2011
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A connection between score matching and denoising autoencoders
Pascal Vincent · 2011
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Practical bayesian optimization of machine learning algorithms
Jasper Snoek, Hugo Larochelle, and Ryan P Adams · 2012
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Input warping for bayesian optimization of non-stationary functions
Jasper Snoek, Kevin Swersky, Rich Zemel, and Ryan Adams · 2014
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Identification and efficient semiparametric estimation of a dynamic discrete game
Patrick Bajari, Victor Chernozhukov, Han Hong, and Denis Nekipelov · 2015
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U-net: Convolutional networks for biomedical image segmentation
Olaf Ronneberger, Philipp Fischer, and Thomas Brox · 2015
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Taking the human out of the loop: A review of bayesian optimization
Bobak Shahriari, Kevin Swersky, Ziyu Wang, Ryan P Adams, and Nando De Freitas · 2015
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Survey of variation in human transcription factors reveals prevalent dna binding changes
Luis A Barrera, Anastasia Vedenko, Jesse V Kurland, Julia M Rogers, Stephen S Gisselbrecht, Elizabeth J Rossin, Jaie Woodard, Luca Mariani, Kian Hong Kock, Sachi Inukai, et al · 2016
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Deep reinforcement learning from human preferences
Paul F Christiano, Jan Leike, Tom Brown, Miljan Martic, Shane Legg, and Dario Amodei · 2017
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Breaking the curse of horizon: Infinite-horizon off-policy estimation
Qiang Liu, Lihong Li, Ziyang Tang, and Dengyong Zhou · 2018
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Conditioning by adaptive sampling for robust design
David Brookes, Hahnbeom Park, and Jennifer Listgarten · 2019
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Information-theoretic considerations in batch reinforcement learning
Jinglin Chen and Nan Jiang · 2019
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On the intrinsic dimensionality of image representations
Sixue Gong, Vishnu Naresh Boddeti, and Anil K Jain · 2019
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Bayesian optimization using deep gaussian processes
Ali Hebbal, Loic Brevault, Mathieu Balesdent, El-Ghazali Talbi, and Nouredine Melab · 2019
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The multichannel pricing dilemma: Do consumers accept higher offline than online prices?
Christian Homburg, Karin Lauer, and Arnd Vomberg · 2019
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User activity measurement in rating-based online-to-offline (o2o) service recommendation
Yuchen Pan, Desheng Wu, Cuicui Luo, and Alexandre Dolgui · 2019
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High-dimensional statistics: A non-asymptotic viewpoint , volume 48
Martin J Wainwright · 2019
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Generative modeling with denoising auto-encoders and langevin sampling
Adam Block, Youssef Mroueh, and Alexander Rakhlin · 2020
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Towards understanding hierarchical learning: Benefits of neural representations
Minshuo Chen, Yu Bai, Jason D Lee, Tuo Zhao, Huan Wang, Caiming Xiong, and Richard Socher · 2020
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Minimax-optimal off-policy evaluation with linear function approximation
Yaqi Duan, Zeyu Jia, and Mengdi Wang · 2020
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A theoretical analysis of deep q-learning
Jianqing Fan, Zhaoran Wang, Yuchen Xie, and Zhuoran Yang · 2020
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Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
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Morel: Model-based offline reinforcement learning
Rahul Kidambi, Aravind Rajeswaran, Praneeth Netrapalli, and Thorsten Joachims · 2020
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Model inversion networks for model-based optimization
Aviral Kumar and Sergey Levine · 2020
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Offline reinforcement learning: Tutorial, review, and perspectives on open problems
Sergey Levine, Aviral Kumar, George Tucker, and Justin Fu · 2020
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Adaptive approximation and generalization of deep neural network with intrinsic dimensionality
Ryumei Nakada and Masaaki Imaizumi · 2020
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A novel recommendation model for online-to-offline service based on the customer network and service location
Yuchen Pan and Desheng Wu · 2020
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Diffusion-lm improves controllable text generation
Xiang Li, John Thickstun, Ishaan Gulrajani, Percy S Liang, and Tatsunori B Hashimoto · 2022
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Training language models to follow instructions with human feedback
Long Ouyang, Jeffrey Wu, Xu Jiang, Diogo Almeida, Carroll Wainwright, Pamela Mishkin, Chong Zhang, Sandhini Agarwal, Katarina Slama, Alex Ray, et al · 2022
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Hierarchical text-conditional image generation with clip latents
Aditya Ramesh, Prafulla Dhariwal, Alex Nichol, Casey Chu, and Mark Chen · 2022
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High-resolution image synthesis with latent diffusion models
Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, and Björn Ommer · 2022
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Face image quality assessment: A literature survey
Torsten Schlett, Christian Rathgeb, Olaf Henniger, Javier Galbally, Julian Fierrez, and Christoph Busch · 2022
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Yang Song and Stefano Ermon · 2020
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Learning to summarize with human feedback
Nisan Stiennon, Long Ouyang, Jeffrey Wu, Daniel Ziegler, Ryan Lowe, Chelsea Voss, Alec Radford, Dario Amodei, and Paul F Christiano · 2020
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Structured denoising diffusion models in discrete state-spaces
Jacob Austin, Daniel D Johnson, Jonathan Ho, Daniel Tarlow, and Rianne van den Berg · 2021
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Offline contextual bandits with overparameterized models
David Brandfonbrener, William Whitney, Rajesh Ranganath, and Joan Bruna · 2021
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Diffusion schrödinger bridge with applications to score-based generative modeling
Valentin De Bortoli, James Thornton, Jeremy Heng, and Arnaud Doucet · 2021
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Diffusion models beat gans on image synthesis
Prafulla Dhariwal and Alexander Nichol · 2021
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Offline model-based optimization via normalized maximum likelihood estimation
Justin Fu and Sergey Levine · 2021
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Christoph Schuhmann, Romain Beaumont, Richard Vencu, Cade Gordon, Ross Wightman, Mehdi Cherti, Theo Coombes, Aarush Katta, Clayton Mullis, Mitchell Wortsman, et al · 2022
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Skill preferences: Learning to extract and execute robotic skills from human feedback
Xiaofei Wang, Kimin Lee, Kourosh Hakhamaneshi, Pieter Abbeel, and Michael Laskin · 2022
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Is conditional generative modeling all you need for decision making?
Anurag Ajay, Yilun Du, Abhi Gupta, Joshua B. Tenenbaum, Tommi S. Jaakkola, and Pulkit Agrawal · 2023
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Stochastic interpolants: A unifying framework for flows and diffusions
Michael S Albergo, Nicholas M Boffi, and Eric Vanden-Eijnden · 2023
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Universal guidance for diffusion models
Arpit Bansal, Hong-Min Chu, Avi Schwarzschild, Soumyadip Sengupta, Micah Goldblum, Jonas Geiping, and Tom Goldstein · 2023
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Linear convergence bounds for diffusion models via stochastic localization
Joe Benton, Valentin De Bortoli, Arnaud Doucet, and George Deligiannidis · 2023
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Offline pricing and demand learning with censored data
Jinzhi Bu, David Simchi-Levi, and Li Wang · 2023
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Spectral ranking inferences based on general multiway comparisons
Jianqing Fan, Zhipeng Lou, Weichen Wang, and Mengxin Yu · 2023
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Diffusion models in bioinformatics and computational biology
Zhiye Guo, Jian Liu, Yanli Wang, Mengrui Chen, Duolin Wang, Dong Xu, and Jianlin Cheng · 2023
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Diffusion models for black-box optimization
Siddarth Krishnamoorthy, Satvik Mehul Mashkaria, and Aditya Grover · 2023
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Generative artificial intelligence in marketing: Applications, opportunities, challenges, and research agenda, 2023
Nir Kshetri, Yogesh K Dwivedi, Thomas H Davenport, and Niki Panteli · 2023
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Reinforcement learning with human feedback: Learning dynamic choices via pessimism
Zihao Li, Zhuoran Yang, and Mengdi Wang · 2023
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Adaptdiffuser: Diffusion models as adaptive self-evolving planners
Zhixuan Liang, Yao Mu, Mingyu Ding, Fei Ni, Masayoshi Tomizuka, and Ping Luo · 2023
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Song Mei and Yuchen Wu · 2023
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Posterior sampling from the spiked models via diffusion processes
Andrea Montanari and Yuchen Wu · 2023
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Diffusion models are minimax optimal distribution estimators
Kazusato Oko, Shunta Akiyama, and Taiji Suzuki · 2023
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The potential of generative artificial intelligence across disciplines: Perspectives and future directions
Keng-Boon Ooi, Garry Wei-Han Tan, Mostafa Al-Emran, Mohammed A Al-Sharafi, Alexandru Capatina, Amrita Chakraborty, Yogesh K Dwivedi, Tzu-Ling Huang, Arpan Kumar Kar, Voon-Hsien Lee, et al · 2023
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Imitating human behaviour with diffusion models
Tim Pearce, Tabish Rashid, Anssi Kanervisto, Dave Bignell, Mingfei Sun, Raluca Georgescu, Sergio Valcarcel Macua, Shan Zheng Tan, Ida Momennejad, Katja Hofmann, and Sam Devlin · 2023
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Yang Song, Prafulla Dhariwal, Mark Chen, and Ilya Sutskever · 2023
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Stylediffusion: Controllable disentangled style transfer via diffusion models, 2023
Zhizhong Wang, Lei Zhao, and Wei Xing · 2023
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De novo design of protein structure and function with rfdiffusion
Joseph L Watson, David Juergens, Nathaniel R Bennett, Brian L Trippe, Jason Yim, Helen E Eisenach, Woody Ahern, Andrew J Borst, Robert J Ragotte, Lukas F Milles, et al · 2023
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Reward-directed conditional diffusion: Provable distribution estimation and reward improvement
Hui Yuan, Kaixuan Huang, Chengzhuo Ni, Minshuo Chen, and Mengdi Wang · 2023
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Adding conditional control to text-to-image diffusion models
Lvmin Zhang and Maneesh Agrawala · 2023
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High-dimensional dueling optimization with preference embedding
Yangwenhui Zhang, Hong Qian, Xiang Shu, and Aimin Zhou · 2023
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Principled reinforcement learning with human feedback from pairwise or k k -wise comparisons
Banghua Zhu, Jiantao Jiao, and Michael I Jordan · 2023
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Diffiqa: Face image quality assessment using denoising diffusion probabilistic models, 2023
Žiga Babnik, Peter Peer, and Vitomir Štruc · 2023
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Scaling rectified flow transformers for high-resolution image synthesis
Patrick Esser, Sumith Kulal, Andreas Blattmann, Rahim Entezari, Jonas Müller, Harry Saini, Yam Levi, Dominik Lorenz, Axel Sauer, Frederic Boesel, et al · 2024
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Sora: A review on background, technology, limitations, and opportunities of large vision models
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Optimal score estimation via empirical bayes smoothing
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