Solution of the propeller conjecture in $ R^3$ - Steven Heilman; Aukosh Jagannath; Assaf Naor (CoRR, 2011)

Solution of the Propeller Conjecture in ℝ3. - Steven Heilman; Aukosh Jagannath; Assaf Naor (Discret. Comput. Geom., 2013)

The Overlap Gap Property in Principal Submatrix Recovery. - David Gamarnik; Aukosh Jagannath; Subhabrata Sen (CoRR, 2019)

Low-Degree Hardness of Random Optimization Problems. - David Gamarnik; Aukosh Jagannath; Alexander S. Wein (FOCS, 2020)

A classification for the performance of online SGD for high-dimensional inference. - Gérard Ben Arous; Reza Gheissari; Aukosh Jagannath (CoRR, 2020)

Graph Convolution for Semi-Supervised Classification: Improved Linear Separability and Out-of-Distribution Generalization. - Aseem Baranwal; Kimon Fountoulakis; Aukosh Jagannath (ICML, 2021)

Circuit Lower Bounds for the p-Spin Optimization Problem. - David Gamarnik; Aukosh Jagannath; Alexander S. Wein (CoRR, 2021)

Online stochastic gradient descent on non-convex losses from high-dimensional inference. - Gérard Ben Arous; Reza Gheissari; Aukosh Jagannath (J. Mach. Learn. Res., 2021)

High-dimensional limit theorems for SGD: Effective dynamics and critical scaling. - Gérard Ben Arous; Reza Gheissari; Aukosh Jagannath (NeurIPS, 2022)

Effects of Graph Convolutions in Deep Networks. - Aseem Baranwal; Kimon Fountoulakis; Aukosh Jagannath (CoRR, 2022)

Concentration of the exponential mechanism and differentially private multivariate medians. - Kelly Ramsay; Aukosh Jagannath; Shoja'eddin Chenouri (CoRR, 2022)

Effects of Graph Convolutions in Multi-layer Networks. - Aseem Baranwal; Kimon Fountoulakis; Aukosh Jagannath (ICLR, 2023)

Optimality of Message-Passing Architectures for Sparse Graphs. - Aseem Baranwal; Kimon Fountoulakis; Aukosh Jagannath (NeurIPS, 2023)

Finding planted cliques using Markov chain Monte Carlo. - Reza Gheissari; Aukosh Jagannath; Yiming Xu (CoRR, 2023)

Graph Attention Retrospective. - Kimon Fountoulakis; Amit Levi; Shenghao Yang 002; Aseem Baranwal; Aukosh Jagannath (J. Mach. Learn. Res., 2023)

High-dimensional SGD aligns with emerging outlier eigenspaces. - Gérard Ben Arous; Reza Gheissari; Jiaoyang Huang; Aukosh Jagannath (ICLR, 2024)

Hardness of Random Optimization Problems for Boolean Circuits, Low-Degree Polynomials, and Langevin Dynamics. - David Gamarnik; Aukosh Jagannath; Alexander S. Wein (SIAM J. Comput., 2024)

An elementary concentration bound for Gibbs measures arising in statistical learning theory. - Kelly Ramsay; Aukosh Jagannath; Shoja'eddin Chenouri (Trans. Mach. Learn. Res., 2025)

Provable Benefits of Unsupervised Pre-training and Transfer Learning via Single-Index Models. - Taj Jones-McCormick; Aukosh Jagannath; Subhabrata Sen (CoRR, 2025)