Publications by Krishna Kumar | EPFL Graph Search

Related publications (8)

Nonbinary Associative Memory With Exponential Pattern Retrieval Capacity and Iterative Learning

Mohammad Amin Shokrollahi, Amir Hesam Salavati, Krishna Kumar

We consider the problem of neural association for a network of nonbinary neurons. Here, the task is to first memorize a set of patterns using a network of neurons whose states assume values from a finite number of integer levels. Later, the same network sh ...

Ieee-Inst Electrical Electronics Engineers Inc2014

Colloidal Atomic Layer Deposition on Nanocrystals Using Ligand-Modified Precursors

Raffaella Buonsanti, Anna Loiudice, Petru Pasquale Albertini, Ona Segura Lecina, Philippe Benjamin Green, Jari Leemans, Mark Adrian Newton, Coline Marie Agathe Boulanger, Krishna Kumar

Atomic layer deposition (ALD) is a method to grow thin metal oxide layers on a variety of materials for applications spanning from electronics to catalysis. Extending ALD to colloidally stable nanocrystals promises to combine the benefits of thin metal oxi ...

Amer Chemical Soc2024

Channel State Feedback Over the MIMO-MAC

Krishna Kumar

In order to exploit the full multiplexing gain of multi-antenna multi-user downlink schemes, accurate channel state information at the transmitter (i.e., at the base station) is required. We consider the design of a closed-loop channel state information fe ...

2011

The Chemical Nature of the Oxide Directs the Stability and Reactivity of Copper|Oxide Interfaces in the Electrochemical CO2 Reduction Reaction

Raffaella Buonsanti, Petru Pasquale Albertini, Jari Leemans, Coline Marie Agathe Boulanger, Krishna Kumar

Understanding the impact of composition and interfaces between metals and oxides is a goal of interest for many chemical reactions. Herein, we propose a framework to map correlations between the electrochemical behavior of the oxide and the stability and r ...

American Chemical Society (ACS)2025

Neural Pre-coding Increases the Pattern Retrieval Capacity of Hopﬁeld and Bidirectional Associative Memories

Wulfram Gerstner, Mohammad Amin Shokrollahi, Amir Hesam Salavati, Krishna Kumar

We consider the problem of neural association, which deals with the retrieval of a previously memorized pattern from its noisy version. The performance of various neural networks developed for this task may be judged in terms of their pattern retrieval cap ...

Ieee Service Center, 445 Hoes Lane, Po Box 1331, Piscataway, Nj 08855-1331 Usa2011

Voltage-driven Chemical Reactions Enable the Synthesis of Tunable Liquid Ga – Metal Nanoparticles

Raffaella Buonsanti, Pascal Alexander Schouwink, Anna Loiudice, Valery Okatenko, Coline Marie Agathe Boulanger, Alexander Nicolas Chen, Krishna Kumar

Nanosized particles of liquid metals are emerging materials which hold promise for applications spanning from microelectronics to catalysis. Yet, the knowledge of their chemical reactivity is largely unknown. Here, we study the reactivity of liquid Ga and ...

2023

Phase Transitions for Mutual Information

Mohammad Amin Shokrollahi, Amir Hesam Salavati, Krishna Kumar

We consider ensembles of binary linear error correcting codes, obtained by sampling each column of the generator matrix G or parity check matrix H independently from the set of all binary vectors of weight d (of appropriate dimension). We investigate the c ...

IEEE2010

Increasing Precursor Reactivity Enables Continuous Tunability of Copper Nanocrystals from Single-Crystalline to Twinned and Stacking Fault-Lined

Noah Isaac Bussell, Raffaella Buonsanti, Anna Loiudice, Petru Pasquale Albertini, Jari Leemans, Coline Marie Agathe Boulanger, Krishna Kumar, Ludovic Emile Frédy Zaza

Colloidal nanocrystals (NCs) are active materials in different applications, wherein their shape dictates their properties, such as optical or catalytic properties, and, thus, their performance. Hence, learning to tune the NC shape is an important goal in ...

2024