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Volodymyr Kuleshov

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DySLIM: Dynamics Stable Learning by Invariant Measure for Chaotic Systems

Feb 06, 2024
Yair Schiff, Zhong Yi Wan, Jeffrey B. Parker, Stephan Hoyer, Volodymyr Kuleshov, Fei Sha, Leonardo Zepeda-Núñez

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QuIP#: Even Better LLM Quantization with Hadamard Incoherence and Lattice Codebooks

Feb 06, 2024
Albert Tseng, Jerry Chee, Qingyao Sun, Volodymyr Kuleshov, Christopher De Sa

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Diffusion Variational Inference: Diffusion Models as Expressive Variational Posteriors

Jan 05, 2024
Top Piriyakulkij, Yingheng Wang, Volodymyr Kuleshov

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Diffusion Models With Learned Adaptive Noise

Dec 20, 2023
Subham Sekhar Sahoo, Aaron Gokaslan, Chris De Sa, Volodymyr Kuleshov

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Active Preference Inference using Language Models and Probabilistic Reasoning

Dec 19, 2023
Top Piriyakulkij, Volodymyr Kuleshov, Kevin Ellis

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CommonCanvas: An Open Diffusion Model Trained with Creative-Commons Images

Oct 25, 2023
Aaron Gokaslan, A. Feder Cooper, Jasmine Collins, Landan Seguin, Austin Jacobson, Mihir Patel, Jonathan Frankle, Cory Stephenson, Volodymyr Kuleshov

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Local Discovery by Partitioning: Polynomial-Time Causal Discovery Around Exposure-Outcome Pairs

Oct 25, 2023
Jacqueline Maasch, Weishen Pan, Shantanu Gupta, Volodymyr Kuleshov, Kyra Gan, Fei Wang

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Text Embeddings Reveal (Almost) As Much As Text

Oct 10, 2023
John X. Morris, Volodymyr Kuleshov, Vitaly Shmatikov, Alexander M. Rush

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ModuLoRA: Finetuning 3-Bit LLMs on Consumer GPUs by Integrating with Modular Quantizers

Sep 28, 2023
Junjie Yin, Jiahao Dong, Yingheng Wang, Christopher De Sa, Volodymyr Kuleshov

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QuIP: 2-Bit Quantization of Large Language Models With Guarantees

Jul 25, 2023
Jerry Chee, Yaohui Cai, Volodymyr Kuleshov, Christopher De Sa

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