Zobrazeno 1 - 10
of 22
pro vyhledávání: '"Bhatnagar, Aadyot"'
The conditional generation of proteins with desired functions and/or properties is a key goal for generative models. Existing methods based on prompting of language models can generate proteins conditioned on a target functionality, such as a desired
Externí odkaz:
http://arxiv.org/abs/2410.03634
Generative models of macromolecules carry abundant and impactful implications for industrial and biomedical efforts in protein engineering. However, existing methods are currently limited to modeling protein structures or sequences, independently or
Externí odkaz:
http://arxiv.org/abs/2401.06151
We study the problem of uncertainty quantification via prediction sets, in an online setting where the data distribution may vary arbitrarily over time. Recent work develops online conformal prediction techniques that leverage regret minimization alg
Externí odkaz:
http://arxiv.org/abs/2302.07869
Wasserstein autoencoder (WAE) shows that matching two distributions is equivalent to minimizing a simple autoencoder (AE) loss under the constraint that the latent space of this AE matches a pre-specified prior distribution. This latent space distrib
Externí odkaz:
http://arxiv.org/abs/2110.10303
Autor:
Bhatnagar, Aadyot, Kassianik, Paul, Liu, Chenghao, Lan, Tian, Yang, Wenzhuo, Cassius, Rowan, Sahoo, Doyen, Arpit, Devansh, Subramanian, Sri, Woo, Gerald, Saha, Amrita, Jagota, Arun Kumar, Gopalakrishnan, Gokulakrishnan, Singh, Manpreet, Krithika, K C, Maddineni, Sukumar, Cho, Daeki, Zong, Bo, Zhou, Yingbo, Xiong, Caiming, Savarese, Silvio, Hoi, Steven, Wang, Huan
We introduce Merlion, an open-source machine learning library for time series. It features a unified interface for many commonly used models and datasets for anomaly detection and forecasting on both univariate and multivariate time series, along wit
Externí odkaz:
http://arxiv.org/abs/2109.09265
Autor:
Luo, Rachel, Bhatnagar, Aadyot, Bai, Yu, Zhao, Shengjia, Wang, Huan, Xiong, Caiming, Savarese, Silvio, Ermon, Stefano, Schmerling, Edward, Pavone, Marco
Probabilistic classifiers output confidence scores along with their predictions, and these confidence scores should be calibrated, i.e., they should reflect the reliability of the prediction. Confidence scores that minimize standard metrics such as t
Externí odkaz:
http://arxiv.org/abs/2102.10809
Autor:
Wang, Weiran, Wang, Guangsen, Bhatnagar, Aadyot, Zhou, Yingbo, Xiong, Caiming, Socher, Richard
Phones and their context-dependent variants have been the standard modeling units for conventional speech recognition systems, while characters and subwords have demonstrated their effectiveness for end-to-end recognition systems. We investigate the
Externí odkaz:
http://arxiv.org/abs/2004.04290
Autor:
Bhatnagar, Aadyot
Publikováno v:
Electronic Journal of Combinatorics 27 (2020) P1.4
We explore the relation between two natural symmetry properties of voting rules. The first is transitive-symmetry -- the property of invariance to a transitive permutation group -- while the second is the "unbiased" property of every voter having the
Externí odkaz:
http://arxiv.org/abs/1907.01685
We study the problem of learning a good search policy for combinatorial search spaces. We propose retrospective imitation learning, which, after initial training by an expert, improves itself by learning from \textit{retrospective inspections} of its
Externí odkaz:
http://arxiv.org/abs/1804.00846
Autor:
Davis, Hunter C., Ramesh, Pradeep, Bhatnagar, Aadyot, Lee-Gosselin, Audrey, Barry, John F., Glenn, David R., Walsworth, Ronald L., Shapiro, Mikhail G.
Publikováno v:
Nature Communications, 2018
Magnetic resonance imaging (MRI) is a widely used biomedical imaging modality that derives much of its contrast from microscale magnetic field gradients in biological tissues. However, the connection between these sub-voxel field patterns and MRI con
Externí odkaz:
http://arxiv.org/abs/1610.01924