Characterizing the Latent Space of Molecular Deep Generative Models with Persistent Homology Metrics. - Yair Schiff; Vijil Chenthamarakshan; Karthikeyan Natesan Ramamurthy; Payel Das (CoRR, 2020)

Alleviating Noisy Data in Image Captioning with Cooperative Distillation. - Pierre L. Dognin; Igor Melnyk; Youssef Mroueh; Inkit Padhi; Mattia Rigotti; Jarret Ross; Yair Schiff (CoRR, 2020)

Tabular Transformers for Modeling Multivariate Time Series. - Inkit Padhi; Yair Schiff; Igor Melnyk; Mattia Rigotti; Youssef Mroueh; Pierre L. Dognin; Jerret Ross; Ravi Nair; Erik R. Altman (ICASSP, 2021)

Predicting Deep Neural Network Generalization with Perturbation Response Curves. - Yair Schiff; Brian Quanz; Payel Das; Pin-Yu Chen (NeurIPS, 2021)

Gi and Pal Scores: Deep Neural Network Generalization Statistics. - Yair Schiff; Brian Quanz; Payel Das; Pin-Yu Chen (CoRR, 2021)

Augmenting Molecular Deep Generative Models with Topological Data Analysis Representations. - Yair Schiff; Vijil Chenthamarakshan; Samuel C. Hoffman; Karthikeyan Natesan Ramamurthy; Payel Das (ICASSP, 2022)

Cloud-Based Real-Time Molecular Screening Platform with MolFormer. - 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 (ECML/PKDD (6), 2022)

Image Captioning as an Assistive Technology: Lessons Learned from VizWiz 2020 Challenge. - Pierre L. Dognin; Igor Melnyk; Youssef Mroueh; Inkit Padhi; Mattia Rigotti; Jarret Ross; Yair Schiff; Richard A. Young; Brian Belgodere (J. Artif. Intell. Res., 2022)

Optimizing Functionals on the Space of Probabilities with Input Convex Neural Networks. - David Alvarez-Melis; Yair Schiff; Youssef Mroueh (Trans. Mach. Learn. Res., 2022)

Learning with Stochastic Orders. - Carles Domingo-Enrich; Yair Schiff; Youssef Mroueh (ICLR, 2023)

Semi-Parametric Inducing Point Networks and Neural Processes. - Richa Rastogi; Yair Schiff; Alon Hacohen; Zhaozhi Li; Ian Lee; Yuntian Deng; Mert R. Sabuncu; Volodymyr Kuleshov (ICLR, 2023)

Semi-Autoregressive Energy Flows: Exploring Likelihood-Free Training of Normalizing Flows. - Phillip Si; Zeyi Chen; Subham Sekhar Sahoo; Yair Schiff; Volodymyr Kuleshov (ICML, 2023)

InfoDiffusion: Representation Learning Using Information Maximizing Diffusion Models. - Yingheng Wang; Yair Schiff; Aaron Gokaslan; Weishen Pan; Fei Wang 001; Christopher De Sa; Volodymyr Kuleshov (ICML, 2023)

Caduceus: Bi-Directional Equivariant Long-Range DNA Sequence Modeling. - Yair Schiff; Chia-Hsiang Kao; Aaron Gokaslan; Tri Dao; Albert Gu; Volodymyr Kuleshov (ICML, 2024)

DySLIM: Dynamics Stable Learning by Invariant Measure for Chaotic Systems. - Yair Schiff; Zhong Yi Wan; Jeffrey B. Parker; Stephan Hoyer; Volodymyr Kuleshov; Fei Sha; Leonardo Zepeda-Núñez (ICML, 2024)

Simple and Effective Masked Diffusion Language Models. - Subham S. Sahoo; Marianne Arriola; Yair Schiff; Aaron Gokaslan; Edgar Marroquin; Justin T. Chiu; Alexander Rush; Volodymyr Kuleshov (NeurIPS, 2024)

Simple and Effective Masked Diffusion Language Models. - Subham Sekhar Sahoo; Marianne Arriola; Yair Schiff; Aaron Gokaslan; Edgar Marroquin; Justin T. Chiu; Alexander M. Rush; Volodymyr Kuleshov (CoRR, 2024)

Simple Guidance Mechanisms for Discrete Diffusion Models. - Yair Schiff; Subham Sekhar Sahoo; Hao Phung; Guanghan Wang; Sam Boshar; Hugo Dalla-torre; Bernardo P. de Almeida; Alexander Rush; Thomas Pierrot; Volodymyr Kuleshov (CoRR, 2024)

Auditing and Generating Synthetic Data With Controllable Trust Trade-Offs. - Brian Belgodere; Pierre L. Dognin; Adam Ivankay; Igor Melnyk; Youssef Mroueh; Aleksandra Mojsilovic; Jirí Navrátil 001; Apoorva Nitsure; Inkit Padhi; Mattia Rigotti; Jerret Ross; Yair Schiff; et al. (IEEE J. Emerg. Sel. Topics Circuits Syst., 2024)

Simple Guidance Mechanisms for Discrete Diffusion Models. - Yair Schiff; Subham Sekhar Sahoo; Hao Phung; Guanghan Wang; Sam Boshar; Hugo Dalla-torre; Bernardo P. de Almeida; Alexander M. Rush; Thomas Pierrot; Volodymyr Kuleshov (ICLR, 2025)

Remasking Discrete Diffusion Models with Inference-Time Scaling. - Guanghan Wang; Yair Schiff; Subham Sekhar Sahoo; Volodymyr Kuleshov (CoRR, 2025)