◍wovepaper
SearchResearchersInstitutions
Sign in
researcher

Nils Kohring

Technical University of Munich

3 papers hereh-index 492 citations7 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author1
  • middle author2

Across the 3 of 3 papers where every author was matched, so the position is known.

fields
  • cs.GT3
affiliations
  • Technical University of Munich
Homepage

identity via Semantic Scholar / OpenAlex

most citedEquilibrium Learning in Combinatorial Auctions: Computing Approximate Bayesian Nash Equilibria via Pseudogradient Dynamics

6 citations · 7 across the 3 of their papers we have counts for

collaborators
Showing cs.GTShow all

3 papers · 1 filter

cs.GT2023

Equilibrium Computation in Multi-Stage Auctions and Contests

Fabian R. Pieroth, Nils Kohring, Martin Bichler

We compute equilibrium strategies in multi-stage games with continuous signal and action spaces as they are widely used in the management sciences and economics. Examples include s…

cs.GT2023★ 1 cited

Enabling First-Order Gradient-Based Learning for Equilibrium Computation in Markets

Nils Kohring, Fabian R. Pieroth, Martin Bichler

Understanding and analyzing markets is crucial, yet analytical equilibrium solutions remain largely infeasible. Recent breakthroughs in equilibrium computation rely on zeroth-order…

cs.GT2021★ 6 cited

Equilibrium Learning in Combinatorial Auctions: Computing Approximate Bayesian Nash Equilibria via Pseudogradient Dynamics

Stefan Heidekrüger, Paul Sutterer, Nils Kohring +2

Applications of combinatorial auctions (CA) as market mechanisms are prevalent in practice, yet their Bayesian Nash equilibria (BNE) remain poorly understood. Analytical solutions…

◍wovepaper

Papers, researchers and institutions, woven together.

Explore
  • Search
  • Researchers
  • Institutions
Account
  • Library
  • Chat
Data
  • arXiv.org
  • Semantic Scholar
  • OpenAlex
  • Latest RSS
AboutContactPrivacyDevelopersllms.txtopenapi.json
Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.