Griffiths, Thomas

1. Recasting Gradient-Based Meta-Learning as Hierarchical Bayes
   2018/01/26 by Erin Grant, Chelsea Finn, Grant, Erin +7 · 38 citations
   Computer Science · #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Machine Learning and Data Classification
2. The Author-Topic Model for Authors and Documents
   2012/07/11 by Michal Rosen‐Zvi, Rosen-Zvi, Michal, Thomas L. Griffiths +5 · 3 citations
   Computer Science · Social Sciences · #Authorship Attribution and Profiling #Computational and Text Analysis Methods #FOS: Computer and information sciences #Information Retrieval (cs.IR) #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Topic Modeling
3. A Non-Parametric Bayesian Method for Inferring Hidden Causes
   2012/06/27 by Frank Wood, Thomas L. Griffiths, Wood, Frank +3 · 3 citations
   Computer Science · Mathematics · #Artificial Intelligence (cs.AI) #Bayesian Methods and Mixture Models #Bayesian Modeling and Causal Inference #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Statistical Methods and Inference
4. Structured Priors for Structure Learning
   2012/06/27 by Mansinghka, Vikash, Kemp, Charles, Griffiths, Thomas +1 · 2 citations
   #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
5. Evaluating computational models of explanation using human judgments
   2013/09/26 by Michael Pacer, Pacer, Michael, Joseph Jay Williams +7 · 2 citations
   Computer Science · #Bayesian Modeling and Causal Inference #Explainable Artificial Intelligence (XAI) #Topic Modeling
6. Causal Head Gating: A Framework for Interpreting Roles of Attention Heads in Transformers
   2025/05/19 by Nam, Andrew, Conklin, Henry, Yang, Yukang +3 · 2 citations
   #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences