Provable Certificates for Adversarial Examples: Fitting a Ball in the Union of Polytopes. - Matt Jordan; Justin Lewis; Alexandros G. Dimakis (NeurIPS, 2019)

Quantifying Perceptual Distortion of Adversarial Examples. - Matt Jordan; Naren Manoj; Surbhi Goel; Alexandros G. Dimakis (CoRR, 2019)

Exactly Computing the Local Lipschitz Constant of ReLU Networks. - Matt Jordan; Alexandros G. Dimakis (NeurIPS, 2020)

Quarantines as a Targeted Immunization Strategy. - Jessica Hoffmann; Matt Jordan; Constantine Caramanis (CoRR, 2020)

Provable Lipschitz Certification for Generative Models. - Matt Jordan; Alex Dimakis (ICML, 2021)

Inverse Problems Leveraging Pre-trained Contrastive Representations. - Sriram Ravula; Georgios Smyrnis; Matt Jordan; Alexandros G. Dimakis (NeurIPS, 2021)

Zonotope Domains for Lagrangian Neural Network Verification. - Matt Jordan; Jonathan Hayase; Alex Dimakis; Sewoong Oh (NeurIPS, 2022)

DataComp-LM: In search of the next generation of training sets for language models. - Jeffrey Li; Alex Fang; Georgios Smyrnis; Maor Ivgi; Matt Jordan; Samir Yitzhak Gadre; Hritik Bansal; Etash Kumar Guha; Sedrick Scott Keh; Kushal Arora; Saurabh Garg; Rui Xin; et al. (NeurIPS, 2024)

Conditional Generative Models are Sufficient to Sample from Any Causal Effect Estimand. - Md. Musfiqur Rahman; Matt Jordan; Murat Kocaoglu (NeurIPS, 2024)

MINT-1T: Scaling Open-Source Multimodal Data by 10x: A Multimodal Dataset with One Trillion Tokens. - Anas Awadalla; Le Xue; Oscar Lo; Manli Shu; Hannah Lee; Etash Kumar Guha; Matt Jordan; Sheng Shen 001; Mohamed Awadalla; Silvio Savarese; Caiming Xiong; Ran Xu 001; et al. (CoRR, 2024)

25.4 A Micromachined Heterogeneously Integrated Active-Probe Enabling Non-Disruptive In-Situ Measurements from DC to 50GHz. - Jesse Moody; Tyler Liebsch; Patrick Finnegan; Stefan Lepkowski; Robert Costanzo; Mieko Hirabayashi; Matt Jordan; Travis Forbes; Christopher Nordquist (ISSCC, 2025)

2 OLMo 2 Furious. - Team OLMo; Pete Walsh; Luca Soldaini; Dirk Groeneveld; Kyle Lo; Shane Arora; Akshita Bhagia; Yuling Gu; Shengyi Huang; Matt Jordan; Nathan Lambert 001; Dustin Schwenk; et al. (CoRR, 2025)

Datasets, Documents, and Repetitions: The Practicalities of Unequal Data Quality. - Alex Fang; Hadi Pouransari; Matt Jordan; Alexander Toshev; Vaishaal Shankar; Ludwig Schmidt; Tom Gunter (CoRR, 2025)