Social influence and the diffusion of user-created content. - Eytan Bakshy; Brian Karrer; Lada A. Adamic (EC, 2009)

Game-Theoretic Models of Information Overload in Social Networks. - Christian Borgs; Jennifer T. Chayes; Brian Karrer; Brendan Meeder; R. Ravi 001; Ray E. Reagans; Amin Sayedi (WAW, 2010)

Random graphs containing arbitrary distributions of subgraphs - Brian Karrer; M. E. J. Newman (CoRR, 2010)

Stochastic blockmodels and community structure in networks - Brian Karrer; M. E. J. Newman (CoRR, 2010)

We know who you followed last summer: inferring social link creation times in twitter. - Brendan Meeder; Brian Karrer; Amin Sayedi; R. Ravi 001; Christian Borgs; Jennifer T. Chayes (WWW, 2011)

An efficient and principled method for detecting communities in networks - Brian Ball; Brian Karrer; M. E. J. Newman (CoRR, 2011)

Competing epidemics on complex networks - Brian Karrer; M. E. J. Newman (CoRR, 2011)

The Anatomy of the Facebook Social Graph - Johan Ugander; Brian Karrer; Lars Backstrom; Cameron Marlow (CoRR, 2011)

Quantifying the invisible audience in social networks. - Michael S. Bernstein; Eytan Bakshy; Moira Burke; Brian Karrer (CHI, 2013)

Graph cluster randomization: network exposure to multiple universes. - Johan Ugander; Brian Karrer; Lars Backstrom; Jon M. Kleinberg (KDD, 2013)

Coauthorship and citation in scientific publishing - Travis Martin; Brian Ball; Brian Karrer; M. E. J. Newman (CoRR, 2013)

Design and analysis of experiments in networks: Reducing bias from interference. - Dean Eckles; Brian Karrer; Johan Ugander (CoRR, 2014)

Percolation on sparse networks. - Brian Karrer; Mark E. J. Newman; Lenka Zdeborová (CoRR, 2014)

Compressing Graphs and Indexes with Recursive Graph Bisection. - Laxman Dhulipala; Igor Kabiljo; Brian Karrer; Giuseppe Ottaviano; Sergey Pupyrev; Alon Shalita (KDD, 2016)

Social Hash: An Assignment Framework for Optimizing Distributed Systems Operations on Social Networks. - Alon Shalita; Brian Karrer; Igor Kabiljo; Arun Sharma; Alessandro Presta; Aaron Adcock; Herald Kllapi; Michael Stumm (NSDI, 2016)

End-to-end Planning of Fixed Millimeter-Wave Networks. - Tim Danford; Onur Filiz; Jing Huang 020; Brian Karrer; Manohar Paluri; Guan Pang; Vish Ponnampalam; Nicolás Stier Moses; Birce Tezel (CoRR, 2017)

Constrained Bayesian Optimization with Noisy Experiments. - Benjamin Letham; Brian Karrer; Guilherme Ottoni; Eytan Bakshy (CoRR, 2017)

Social Hash Partitioner: A Scalable Distributed Hypergraph Partitioner. - Igor Kabiljo; Brian Karrer; Mayank Pundir; Sergey Pupyrev; Alon Shalita; Yaroslav Akhremtsev; Alessandro Presta (Proc. VLDB Endow., 2017)

BoTorch: Programmable Bayesian Optimization in PyTorch. - Maximilian Balandat; Brian Karrer; Daniel R. Jiang; Samuel Daulton; Benjamin Letham; Andrew Gordon Wilson; Eytan Bakshy (CoRR, 2019)

Efficient Nonmyopic Bayesian Optimization via One-Shot Multi-Step Trees. - Shali Jiang 001; Daniel R. Jiang; Maximilian Balandat; Brian Karrer; Jacob R. Gardner; Roman Garnett (NeurIPS, 2020)

BoTorch: A Framework for Efficient Monte-Carlo Bayesian Optimization. - Maximilian Balandat; Brian Karrer; Daniel R. Jiang; Samuel Daulton; Benjamin Letham; Andrew Gordon Wilson; Eytan Bakshy (NeurIPS, 2020)

Network Experimentation at Scale. - Brian Karrer; Liang Shi; Monica Bhole; Matt Goldman; Tyrone Palmer; Charlie Gelman; Mikael Konutgan; Feng Sun (KDD, 2021)

The Decoupled Extended Kalman Filter for Dynamic Exponential-Family Factorization Models. - Carlos Alberto Gomez-Uribe; Brian Karrer (J. Mach. Learn. Res., 2021)

Bounding Training Data Reconstruction in Private (Deep) Learning. - Chuan Guo 001; Brian Karrer; Kamalika Chaudhuri; Laurens van der Maaten (ICML, 2022)

Voicebox: Text-Guided Multilingual Universal Speech Generation at Scale. - Matthew Le 001; Apoorv Vyas; Bowen Shi; Brian Karrer; Leda Sari; Rashel Moritz; Mary Williamson; Vimal Manohar; Yossi Adi; Jay Mahadeokar; Wei-Ning Hsu (NeurIPS, 2023)

HHVM Performance Optimization for Large Scale Web Services. - Yuhao Li; Abhishek Gupta; Alex Yang; Peinan Chen; Joey Pinto; Brian Karrer; Mayank Pundir; Maximilian Balandat; Arun Kejariwal; Benjamin C. Lee (ICPE, 2023)

Privately generating tabular data using language models. - Alexandre Sablayrolles; Yue Wang; Brian Karrer (CoRR, 2023)

Scaling Autoregressive Multi-Modal Models: Pretraining and Instruction Tuning. - Lili Yu; Bowen Shi; Ramakanth Pasunuru; Benjamin Muller; Olga Golovneva; Tianlu Wang; Arun Babu; Binh Tang; Brian Karrer; Shelly Sheynin; Candace Ross; Adam Polyak; et al. (CoRR, 2023)

Training-free Linear Image Inversion via Flows. - Ashwini Pokle; Matthew J. Muckley; Ricky T. Q. Chen; Brian Karrer (CoRR, 2023)

Generalized Schrödinger Bridge Matching. - Guan-Horng Liu; Yaron Lipman; Maximilian Nickel; Brian Karrer; Evangelos A. Theodorou; Ricky T. Q. Chen (ICLR, 2024)

D-Flow: Differentiating through Flows for Controlled Generation. - Heli Ben-Hamu; Omri Puny; Itai Gat; Brian Karrer; Uriel Singer; Yaron Lipman (ICML, 2024)

Sense and Sensitivity: Evaluating the simulation of social dynamics via Large Language Models. - Da Ju; Adina Williams; Brian Karrer; Maximilian Nickel (CoRR, 2024)

Flow Matching Guide and Code. - Yaron Lipman; Marton Havasi; Peter Holderrieth; Neta Shaul; Matt Le 001; Brian Karrer; Ricky T. Q. Chen; David Lopez-Paz; Heli Ben-Hamu; Itai Gat (CoRR, 2024)

Exact Privacy Analysis of the Gaussian Sparse Histogram Mechanism. - Arjun Wilkins; Daniel Kifer; Danfeng Zhang; Brian Karrer (J. Priv. Confidentiality, 2024)

Training-free linear image inverses via flows. - Ashwini Pokle; Matthew J. Muckley; Ricky T. Q. Chen; Brian Karrer (Trans. Mach. Learn. Res., 2024)

Enhancing and Evaluating Probabilistic Circuits for High-Resolution Lossless Image Compression. - Daniel Severo 001; Jingtong Su; Anji Liu; Jeff Johnson; Brian Karrer; Guy Van den Broeck; Matthew J. Muckley; Karen Ullrich (DCC, 2025)

Adjoint Matching: Fine-tuning Flow and Diffusion Generative Models with Memoryless Stochastic Optimal Control. - Carles Domingo-Enrich; Michal Drozdzal; Brian Karrer; Ricky T. Q. Chen (ICLR, 2025)

Generator Matching: Generative modeling with arbitrary Markov processes. - Peter Holderrieth; Marton Havasi; Jason Yim; Neta Shaul; Itai Gat; Tommi S. Jaakkola; Brian Karrer; Ricky T. Q. Chen; Yaron Lipman (ICLR, 2025)

Flow Matching with General Discrete Paths: A Kinetic-Optimal Perspective. - Neta Shaul; Itai Gat; Marton Havasi; Daniel Severo 001; Anuroop Sriram; Peter Holderrieth; Brian Karrer; Yaron Lipman; Ricky T. Q. Chen (ICLR, 2025)

Adjoint Sampling: Highly Scalable Diffusion Samplers via Adjoint Matching. - Aaron J. Havens; Benjamin Kurt Miller; Bing Yan; Carles Domingo-Enrich; Anuroop Sriram; Brandon M. Wood; Daniel Levine; Bin Hu; Brandon Amos; Brian Karrer; Xiang Fu 005; Guan-Horng Liu; et al. (CoRR, 2025)

Learning Distributions over Permutations and Rankings with Factorized Representations. - Daniel Severo 001; Brian Karrer; Niklas Nolte (CoRR, 2025)

Accelerated Sampling from Masked Diffusion Models via Entropy Bounded Unmasking. - Heli Ben-Hamu; Itai Gat; Daniel Severo 001; Niklas Nolte; Brian Karrer (CoRR, 2025)

Edit Flows: Flow Matching with Edit Operations. - Marton Havasi; Brian Karrer; Itai Gat; Ricky T. Q. Chen (CoRR, 2025)