658 citations · 2.2k across the 187 of their papers we have counts for
11 papers · 1 filter
Finding the root in random nearest neighbor trees
Anna Brandenberger, Cassandra Marcussen, Elchanan Mossel +1
We study the inference of network archaeology in growing random geometric graphs. We consider the root finding problem for a random nearest neighbor tree in dimension $d \in \mathb…
Comparison Theorems for the Mixing Times of Systematic and Random Scan Dynamics
Jason Gaitonde, Elchanan Mossel
A popular method for sampling from high-dimensional distributions is the \emph{Gibbs sampler}, which iteratively resamples sites from the conditional distribution of the desired me…
Bypassing the Noisy Parity Barrier: Learning Higher-Order Markov Random Fields from Dynamics
Jason Gaitonde, Ankur Moitra, Elchanan Mossel
We consider the problem of learning graphical models, also known as Markov random fields (MRFs) from temporally correlated samples. As in many traditional statistical settings, fun…
Multiplayer Games of War
Axel Adjei, Neil Krishnan, Elchanan Mossel
A recent paper by Bhatia, Chin, Mani, and Mossel (2026) defined stochastic processes modeling the game of War for {\em two players} with cards. That paper showed that these mod…
Weak recovery, hypothesis testing, and mutual information in stochastic block models and planted factor graphs
Elchanan Mossel, Allan Sly, Youngtak Sohn
The stochastic block model is a canonical model of communities in random graphs. It was introduced in the social sciences and statistics as a model of communities, and in theoretic…
Monotonicity, Topology, and Convexity of Recurrence in Random Walks
Rupert Li, Elchanan Mossel, Benjamin Weiss
We consider non-homogeneous random walks on the two-dimensional positive quadrant and the one-dimensional slab . In the 1960's the f…
Finding Super-spreaders in Network Cascades
Elchanan Mossel, Anirudh Sridhar
Suppose that a cascade (e.g., an epidemic) spreads on an unknown graph, and only the infection times of vertices are observed. What can be learned about the graph from the infectio…
Sample-Efficient Linear Regression with Self-Selection Bias
Jason Gaitonde, Elchanan Mossel
We consider the problem of linear regression with self-selection bias in the unknown-index setting, as introduced in recent work by Cherapanamjeri, Daskalakis, Ilyas, and Zampetaki…
Low Degree Hardness for Broadcasting on Trees
Han Huang, Elchanan Mossel
We study the low-degree hardness of broadcasting on trees. Broadcasting on trees has been extensively studied in statistical physics, in computational biology in relation to phylog…
Gaussian Broadcast on Grids
Pakawut Jiradilok, Elchanan Mossel
Motivated by the classical work on finite noisy automata (Gray 1982, Gács 2001, Gray 2001) and by the recent work on broadcasting on grids (Makur, Mossel, and Polyanskiy 2022), we…
Reconstructing the Geometry of Random Geometric Graphs
Han Huang, Pakawut Jiradilok, Elchanan Mossel
Random geometric graphs are random graph models defined on metric spaces. Such a model is defined by first sampling points from a metric space and then connecting each pair of samp…