118 citations · 152 across the 14 of their papers we have counts for
16 papers
Origins and mitigation of double descent in reduced order modeling
Andrei A. Klishin, J. Nathan Kutz, Krithika Manohar
Latent low-dimensional structure in datasets of natural and engineered systems enables their sparse sensing, or full-state reconstruction from historical data and very few carefull…
From STLS to Projection-based Dictionary Selection in Sparse Regression for System Identification
Hangjun Cho, Fabio V. G. Amaral, Andrei A. Klishin +2
In this work, we revisit dictionary-based sparse regression, in particular, Sequential Threshold Least Squares (STLS), and propose a score-guided library selection to provide pract…
PySensors 2.0: A Python Package for Sparse Sensor Placement
Niharika Karnik, Yash Bhangale, Mohammad G. Abdo +6
PySensors is a Python package for selecting and placing a sparse set of sensors for reconstruction and classification tasks. In this major update to PySensors, we introduce spatial…
Statistical Mechanics of Dynamical System Identification
Andrei A. Klishin, Joseph Bakarji, J. Nathan Kutz +1
Recovering dynamical equations from observed noisy data is the central challenge of system identification. We develop a statistical mechanics approach to analyze sparse equation di…
Human Learning of Hierarchical Graphs
Xiaohuan Xia, Andrei A. Klishin, Jennifer Stiso +4
Humans are constantly exposed to sequences of events in the environment. Those sequences frequently evince statistical regularities, such as the probabilities with which one event…
No Free Lunch for Avoiding Clustering Vulnerabilities in Distributed Systems
Pheerawich Chitnelawong, Andrei A. Klishin, Norman MacKay +2
Emergent design failures are ubiquitous in complex systems, and often arise when system elements cluster. Approaches to systematically reduce clustering could improve a design's re…
Data-Induced Interactions of Sparse Sensors Using Statistical Physics
Andrei A. Klishin, J. Nathan Kutz, Krithika Manohar
Large-dimensional empirical data in science and engineering frequently have a low-rank structure and can be represented as a combination of just a few eigenmodes. Because of this s…
Learning Dynamic Graphs, Too Slow
Andrei A. Klishin, Nicolas H. Christianson, Cynthia S. Q. Siew +1
The structure of knowledge is commonly described as a network of key concepts and semantic relations between them. A learner of a particular domain can discover this network by nav…
Exposure theory for learning complex networks with random walks
Andrei A. Klishin, Dani S. Bassett
Random walks are a common model for exploration and discovery of complex networks. While numerous algorithms have been proposed to map out an unknown network, a complementary quest…
Citation inequity and gendered citation practices in contemporary physics
Erin G. Teich, Jason Z. Kim, Christopher W. Lynn +8
The historical and contemporary under-attribution of women's contributions to scientific scholarship is well-known and well-studied, with effects that are felt today in myriad ways…
Optimizing the Human Learnability of Abstract Network Representations
William Qian, Christopher W. Lynn, Andrei A. Klishin +3
Precisely how humans process relational patterns of information in knowledge, language, music, and society is not well understood. Prior work in the field of statistical learning h…
Topological Design of Heterogeneous Self-Assembly
Andrei A. Klishin, Michael P. Brenner
Controlling the topology of structures self-assembled from a set of heterogeneous building blocks is highly desirable for many applications, but is poorly understood theoretically.…
Avoidance, Adjacency, and Association in Distributed Systems Design
Andrei A. Klishin, David J. Singer, Greg van Anders
Patterns of avoidance, adjacency, and association in complex systems design emerge from the system's underlying logical architecture (functional relationships among components) and…
Robust Design from Systems Physics
Andrei A. Klishin, Alec Kirkley, David J. Singer +1
A crucial challenge in engineering modern, integrated systems is to produce robust designs. Ensuring robust design is difficult because subsystem couplings produce unpredictable re…
Statistical Physics of Design
Andrei A. Klishin, Colin P. F. Shields, David J. Singer +1
A key challenge in complex design problems that permeate science and engineering is the need to balance design objectives for specific design elements or subsystems with global sys…
Explaining the stellar initial mass function with the theory of spatial networks
Andrei Klishin, Igor Chilingarian
The distributions of stars and prestellar cores by mass (initial and dense core mass functions, IMF/DCMF) are among the key factors regulating star formation and are the subject of…