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Yair Schiff
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2020 – today
- 2024
- [c10]Yair Schiff, Chia-Hsiang Kao, Aaron Gokaslan, Tri Dao, Albert Gu, Volodymyr Kuleshov:
Caduceus: Bi-Directional Equivariant Long-Range DNA Sequence Modeling. ICML 2024 - [c9]Yair Schiff, Zhong Yi Wan, Jeffrey B. Parker, Stephan Hoyer, Volodymyr Kuleshov, Fei Sha, Leonardo Zepeda-Núñez:
DySLIM: Dynamics Stable Learning by Invariant Measure for Chaotic Systems. ICML 2024 - [i15]Yair Schiff, Zhong Yi Wan, Jeffrey B. Parker, Stephan Hoyer, Volodymyr Kuleshov, Fei Sha, Leonardo Zepeda-Núñez:
DySLIM: Dynamics Stable Learning by Invariant Measure for Chaotic Systems. CoRR abs/2402.04467 (2024) - [i14]Yair Schiff, Chia-Hsiang Kao, Aaron Gokaslan, Tri Dao, Albert Gu, Volodymyr Kuleshov:
Caduceus: Bi-Directional Equivariant Long-Range DNA Sequence Modeling. CoRR abs/2403.03234 (2024) - [i13]Subham Sekhar Sahoo, Marianne Arriola, Yair Schiff, Aaron Gokaslan, Edgar Marroquin, Justin T. Chiu, Alexander M. Rush, Volodymyr Kuleshov:
Simple and Effective Masked Diffusion Language Models. CoRR abs/2406.07524 (2024) - 2023
- [c8]Carles Domingo-Enrich, Yair Schiff, Youssef Mroueh:
Learning with Stochastic Orders. ICLR 2023 - [c7]Richa Rastogi, Yair Schiff, Alon Hacohen, Zhaozhi Li, Ian Lee, Yuntian Deng, Mert R. Sabuncu, Volodymyr Kuleshov:
Semi-Parametric Inducing Point Networks and Neural Processes. ICLR 2023 - [c6]Phillip Si, Zeyi Chen, Subham Sekhar Sahoo, Yair Schiff, Volodymyr Kuleshov:
Semi-Autoregressive Energy Flows: Exploring Likelihood-Free Training of Normalizing Flows. ICML 2023: 31732-31753 - [c5]Yingheng Wang, Yair Schiff, Aaron Gokaslan, Weishen Pan, Fei Wang, Christopher De Sa, Volodymyr Kuleshov:
InfoDiffusion: Representation Learning Using Information Maximizing Diffusion Models. ICML 2023: 36336-36354 - [i12]Brian Belgodere, Pierre L. Dognin, Adam Ivankay, Igor Melnyk, Youssef Mroueh, Aleksandra Mojsilovic, Jirí Navrátil, Apoorva Nitsure, Inkit Padhi, Mattia Rigotti, Jerret Ross, Yair Schiff, Radhika Vedpathak, Richard A. Young:
Auditing and Generating Synthetic Data with Controllable Trust Trade-offs. CoRR abs/2304.10819 (2023) - [i11]Yingheng Wang, Yair Schiff, Aaron Gokaslan, Weishen Pan, Fei Wang, Christopher De Sa, Volodymyr Kuleshov:
InfoDiffusion: Representation Learning Using Information Maximizing Diffusion Models. CoRR abs/2306.08757 (2023) - 2022
- [j2]Pierre L. Dognin, Igor Melnyk, Youssef Mroueh, Inkit Padhi, Mattia Rigotti
, Jarret Ross, Yair Schiff, Richard A. Young, Brian Belgodere:
Image Captioning as an Assistive Technology: Lessons Learned from VizWiz 2020 Challenge. J. Artif. Intell. Res. 73: 437-459 (2022) - [j1]David Alvarez-Melis, Yair Schiff, Youssef Mroueh:
Optimizing Functionals on the Space of Probabilities with Input Convex Neural Networks. Trans. Mach. Learn. Res. 2022 (2022) - [c4]Yair Schiff, Vijil Chenthamarakshan, Samuel C. Hoffman, Karthikeyan Natesan Ramamurthy, Payel Das:
Augmenting Molecular Deep Generative Models with Topological Data Analysis Representations. ICASSP 2022: 3783-3787 - [c3]Brian Belgodere, Vijil Chenthamarakshan, Payel Das, Pierre L. Dognin, Toby Kurien, Igor Melnyk, Youssef Mroueh, Inkit Padhi, Mattia Rigotti, Jarret Ross, Yair Schiff, Richard A. Young:
Cloud-Based Real-Time Molecular Screening Platform with MolFormer. ECML/PKDD (6) 2022: 641-644 - [i10]Carles Domingo-Enrich, Yair Schiff, Youssef Mroueh:
Learning with Stochastic Orders. CoRR abs/2205.13684 (2022) - [i9]Brian Belgodere, Vijil Chenthamarakshan, Payel Das, Pierre L. Dognin, Toby Kurien, Igor Melnyk, Youssef Mroueh, Inkit Padhi, Mattia Rigotti
Cloud-Based Real-Time Molecular Screening Platform with MolFormer. CoRR abs/2208.06665 (2022) - 2021
- [c2]Inkit Padhi, Yair Schiff, Igor Melnyk, Mattia Rigotti
Tabular Transformers for Modeling Multivariate Time Series. ICASSP 2021: 3565-3569 - [c1]Yair Schiff, Brian Quanz, Payel Das, Pin-Yu Chen:
Predicting Deep Neural Network Generalization with Perturbation Response Curves. NeurIPS 2021: 21176-21188 - [i8]Yair Schiff, Brian Quanz, Payel Das, Pin-Yu Chen:
Gi and Pal Scores: Deep Neural Network Generalization Statistics. CoRR abs/2104.03469 (2021) - [i7]David Alvarez-Melis, Yair Schiff, Youssef Mroueh:
Optimizing Functionals on the Space of Probabilities with Input Convex Neural Networks. CoRR abs/2106.00774 (2021) - [i6]Yair Schiff, Vijil Chenthamarakshan, Samuel C. Hoffman, Karthikeyan Natesan Ramamurthy, Payel Das:
Augmenting Molecular Deep Generative Models with Topological Data Analysis Representations. CoRR abs/2106.04464 (2021) - [i5]Yair Schiff, Brian Quanz, Payel Das, Pin-Yu Chen:
Predicting Deep Neural Network Generalization with Perturbation Response Curves. CoRR abs/2106.04765 (2021) - 2020
- [i4]Yair Schiff, Vijil Chenthamarakshan, Karthikeyan Natesan Ramamurthy, Payel Das:
Characterizing the Latent Space of Molecular Deep Generative Models with Persistent Homology Metrics. CoRR abs/2010.08548 (2020) - [i3]Inkit Padhi, Yair Schiff, Igor Melnyk, Mattia Rigotti, Youssef Mroueh, Pierre L. Dognin, Jerret Ross, Ravi Nair, Erik R. Altman:
Tabular Transformers for Modeling Multivariate Time Series. CoRR abs/2011.01843 (2020) - [i2]Pierre L. Dognin, Igor Melnyk, Youssef Mroueh, Inkit Padhi, Mattia Rigotti, Jarret Ross, Yair Schiff:
Alleviating Noisy Data in Image Captioning with Cooperative Distillation. CoRR abs/2012.11691 (2020) - [i1]Pierre L. Dognin, Igor Melnyk, Youssef Mroueh, Inkit Padhi, Mattia Rigotti, Jarret Ross, Yair Schiff, Richard A. Young, Brian Belgodere:
Image Captioning as an Assistive Technology: Lessons Learned from VizWiz 2020 Challenge. CoRR abs/2012.11696 (2020)
Coauthor Index
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