Replacing Mark Bits with Randomness in Fibonacci Heaps. - Jerry Li 001; John Peebles (ICALP (1), 2015)

Faster Algorithms for Computing the Stationary Distribution, Simulating Random Walks, and More. - Michael B. Cohen; Jonathan A. Kelner; John Peebles; Richard Peng; Aaron Sidford; Adrian Vladu (FOCS, 2016)

Sublinear-Time Algorithms for Counting Star Subgraphs with Applications to Join Selectivity Estimation. - Maryam Aliakbarpour; Amartya Shankha Biswas; Themistoklis Gouleakis; John Peebles; Ronitt Rubinfeld; Anak Yodpinyanee (CoRR, 2016)

Determinant-Preserving Sparsification of SDDM Matrices with Applications to Counting and Sampling Spanning Trees. - David Durfee; John Peebles; Richard Peng; Anup B. Rao (FOCS, 2017)

Almost-linear-time algorithms for Markov chains and new spectral primitives for directed graphs. - Michael B. Cohen; Jonathan A. Kelner; John Peebles; Richard Peng; Anup B. Rao; Aaron Sidford; Adrian Vladu (STOC, 2017)

Sampling random spanning trees faster than matrix multiplication. - David Durfee; Rasmus Kyng; John Peebles; Anup B. Rao; Sushant Sachdeva (STOC, 2017)

Towards Understanding the Dynamics of Generative Adversarial Networks. - Jerry Li 001; Aleksander Madry; John Peebles; Ludwig Schmidt (CoRR, 2017)

Sample-Optimal Identity Testing with High Probability. - Ilias Diakonikolas; Themis Gouleakis; John Peebles; Eric Price 001 (Electron. Colloquium Comput. Complex., 2017)

Solving Directed Laplacian Systems in Nearly-Linear Time through Sparse LU Factorizations. - Michael B. Cohen; Jonathan A. Kelner; Rasmus Kyng; John Peebles; Richard Peng; Anup B. Rao; Aaron Sidford (FOCS, 2018)

On the Limitations of First-Order Approximation in GAN Dynamics. - Jerry Li 001; Aleksander Madry; John Peebles; Ludwig Schmidt (ICML, 2018)

Sublinear-Time Algorithms for Counting Star Subgraphs via Edge Sampling. - Maryam Aliakbarpour; Amartya Shankha Biswas; Themis Gouleakis; John Peebles; Ronitt Rubinfeld; Anak Yodpinyanee (Algorithmica, 2018)

Towards Testing Monotonicity of Distributions Over General Posets. - Maryam Aliakbarpour; Themis Gouleakis; John Peebles; Ronitt Rubinfeld; Anak Yodpinyanee (COLT, 2019)

Testing Identity of Multidimensional Histograms. - Ilias Diakonikolas; Daniel M. Kane; John Peebles (COLT, 2019)

Collision-Based Testers are Optimal for Uniformity and Closeness. - Ilias Diakonikolas; Themis Gouleakis; John Peebles; Eric Price 001 (Chic. J. Theor. Comput. Sci., 2019)

The Hessian Penalty: A Weak Prior for Unsupervised Disentanglement. - William S. Peebles; John Peebles; Jun-Yan Zhu; Alexei A. Efros; Antonio Torralba 001 (ECCV (6), 2020)

High-precision Estimation of Random Walks in Small Space. - AmirMahdi Ahmadinejad; Jonathan A. Kelner; Jack Murtagh; John Peebles; Aaron Sidford; Salil P. Vadhan (FOCS, 2020)

Optimal Testing of Discrete Distributions with High Probability. - Ilias Diakonikolas; Themis Gouleakis; Daniel Kane 001; John Peebles; Eric Price 001 (Electron. Colloquium Comput. Complex., 2020)

Determinant-Preserving Sparsification of SDDM Matrices. - David Durfee; John Peebles; Richard Peng; Anup B. Rao (SIAM J. Comput., 2020)

Efficient Approximation Algorithms for the Inverse Semivalue Problem. - Ilias Diakonikolas; Chrystalla Pavlou; John Peebles; Alistair Stewart (AAMAS, 2022)

Singular Value Approximation and Sparsifying Random Walks on Directed Graphs. - AmirMahdi Ahmadinejad; John Peebles; Edward Pyne; Aaron Sidford; Salil P. Vadhan (FOCS, 2023)

Singular Value Approximation and Reducing Directed to Undirected Graph Sparsification. - AmirMahdi Ahmadinejad; John Peebles; Edward Pyne; Aaron Sidford; Salil P. Vadhan (CoRR, 2023)

Apple Intelligence Foundation Language Models. - Tom Gunter; Zirui Wang; Chong Wang; Ruoming Pang; Andy Narayanan; Aonan Zhang; Bowen Zhang 002; Chen Chen 005; Chung-Cheng Chiu; David Qiu; Deepak Gopinath; Dian Ang Yap; et al. (CoRR, 2024)

AXLearn: Modular Large Model Training on Heterogeneous Infrastructure. - Mark Lee; Tom Gunter; Chang Lan; John Peebles; Hanzhi Zhou; Kelvin Zou; Sneha Bangalore; Chung-Cheng Chiu; Nan Du; Xianzhi Du; Philipp Dufter; Ruixuan Hou; et al. (CoRR, 2025)

Apple Intelligence Foundation Language Models: Tech Report 2025. - Hanzhi Zhou; Erik Hornberger; Pengsheng Guo; Xiyou Zhou; Saiwen Wang; Xin Wang; Yifei He; Xuankai Chang; Rene Rauch; Louis D'hauwe; John Peebles; Alec Doane; et al. (CoRR, 2025)