35 citations · 50 across the 15 of their papers we have counts for
8 papers · 1 filter
Mechanisms of Resistive Switching in 2D Monolayer and Multilayer Materials
M. Kaniselvan, Y. R. Jeon, M. Mladenović +2
The power and energy consumption of resistive switching devices can be lowered by reducing their active layer dimensions. Efforts to push this low-energy switching property to its…
Reinforcement Learning Improves Traversal of Parametric Knowledge in LLMs
Renfei Zhang, Manasa Kaniselvan, Rylan Schaeffer +1
Reinforcement learning (RL) is often credited with improving reasoning at the expense of factual knowledge. We instead find that reasoning models outperform their instruction-tuned…
Enhancing Diffusion-Based Sampling with Molecular Collective Variables
Juno Nam, Bálint Máté, Artur P. Toshev +6
Diffusion-based samplers learn to sample complex, high-dimensional distributions using energies or log densities alone, without training data. Yet, they remain impractical for mole…
Learning from the electronic structure of molecules across the periodic table
Manasa Kaniselvan, Benjamin Kurt Miller, Meng Gao +2
Machine-Learned Interatomic Potentials (MLIPs) require vast amounts of atomic structure data to learn forces and energies, and their performance continues to improve with training…
Distributed Equivariant Graph Neural Networks for Large-Scale Electronic Structure Prediction
Manasa Kaniselvan, Alexander Maeder, Chen Hao Xia +2
Equivariant Graph Neural Networks (eGNNs) trained on density-functional theory (DFT) data can potentially perform electronic structure prediction at unprecedented scales, enabling…
Termination-Dependent Resistive Switching in SrTiO Valence Change Memory Cells
Marko Mladenović, Manasa Kaniselvan, Christoph Weilenmann +2
Valence change memory (VCM) cells based on SrTiO (STO), a perovskite oxide, are a promising type of emerging memory device. While the operational principle of most VCM cells re…
Electroforming Kinetics in HfOx/Ti RRAM: Mechanisms Behind Compositional and Thermal Engineering
Manasa Kaniselvan, Kevin Portner, Donato Francesco Falcone +6
A critical issue affecting filamentary resistive random access memory (RRAM) cells is the requirement of high voltages during electroforming. Reducing the magnitude of these voltag…
Learning the Electronic Hamiltonian of Large Atomic Structures
Chen Hao Xia, Manasa Kaniselvan, Alexandros Nikolaos Ziogas +4
Graph neural networks (GNNs) have shown promise in learning the ground-state electronic properties of materials, subverting ab initio density functional theory (DFT) calculations w…