An updated version can be found here

Research interests

I focus on understanding and predicting decisions using quantitative modeling and advanced statistics / machine learning. My models of decision-making rely on insights from many fields: Neuroscience, Cognitive and Mathematical Psychology, Genomics, Economics and Computer Science.

  • Econometrics / Machine Learning
    • Neural Networks
    • Bayesian Methods and Computational Statistics
    • Big Data and High Performance Computing (HPC)
  • Quantitative Marketing
    • Demand analysis
    • Quantitative Behavioral Modelization and Decision Processes
    • Consumer Neuroscience and Consumer Genomics
  • Behavioral Neuro-Genomics

Work in Progress

"Bayesian Deep Learning for Small Datasets: Predicting Sales from Bottle Design",
Remi Daviet

"Foundations of the Decoy Effect: Putting Theory to the Test",
Ulrich Bergmann, Remi Daviet, Ernst Fehr

"Social Preference Estimation Using Adaptive Experimental Design",
Taisuke Imai, Devdeepta Bose, Remi Daviet, Gidi Nave, Colin Camerer
Submitted for pre-results review.

"Analyzing Normalization Models of Choice with Sequential Optimal Inference",
Remi Daviet

Papers and publications

In Marketing

"The Consumer DNA Revolution: Why Marketers Should Care About Genomic Data",
Remi Daviet, Gideon Nave, Yoram Wind
R&R, Journal of Marketing, draft available on demand.

"Neural Attribute Normalization: An Application to Marketing with Deep Learning",
Remi Daviet
draft available on demand

"Hamiltonian Sequential Monte-Carlo: Application to Consumer Demand",
Martin Burda, Remi Daviet
R&R, Latest version

"A Double Decoy Experiment to Distinguish Theories of Dominance",
Remi Daviet, Ryan Webb

In Methodology

"Sequential Optimal Inference for Experiments with Bayesian Particle Filters",
Remi Daviet
Latest version

"Sequential Monte Carlo for Hierarchical Bayes with Large Datasets",
Remi Daviet
Latest version

"Multialternative Drift Diffusion Model: Estimation with Hit and Run Particles",
Remi Daviet
Draft available on demand.

"Inference with Hamiltonian Sequential Monte Carlo Simulators",
Remi Daviet
Latest version , C++/CUDA code

In Behavioral Neuro-Genomics and Consumer Neuroscience

"Genetic underpinnings of risky behavior relate to altered neuroanatomy",
Gökhan Aydogan, Remi Daviet, Gideon Nave, Philipp Koellinger et Al.
Submitted, Latest version, Pre-registered with the Open Science Framework

"Reflecting on the Evidence. A reply to Knight et al. (2019)",
Gideon Nave*, Remi Daviet*, Amos Nadler, David Zava, Colin Camerer (* for equal contribution)
R&R, Psychological Science

"Multimodal brain imaging in the UK Biobank reveals new associations between alcohol intake and brain structure",
Remi Daviet, Gideon Nave, Philipp Koellinger, Reagan Wetherill et Al.
Draft available on request, Pre-registered with the Open Science Framework


"Methods for statistical analysis and prediction of discrete choices"
Published version

  • Chapter 1: Attribute Divisive Normalization : A Neural Decision Model for Discrete Choice
  • Chapter 2: Hamiltonian Sequential Monte Carlo with Application to Consumer Choice Behavior
  • Chapter 3: Sequential Optimal Inference for Experiments with Sequential Monte Carlo Methods