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Kneib, Thomas

  1. Neural Additive Models for Location Scale and Shape: A Framework for Interpretable Neural Regression Beyond the Mean
    2023/01/27 by Thielmann, Anton, Kruse, René-Marcel, Kneib, Thomas +1 · 5 citations
    #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  2. Nonparametric inference in hidden Markov models using P-splines
    2013/09/02 by Roland Langrock, Thomas Kneib, Langrock, Roland +5 · 2 citations
    Computer Science · Earth and Planetary Sciences · #Bayesian Methods and Mixture Models #FOS: Computer and information sciences #Methodology (stat.ME) #Target Tracking and Data Fusion in Sensor Networks #Underwater Acoustics Research
  3. Markov-switching generalized additive models
    2014/06/14 by Roland Langrock, Langrock, Roland, Thomas Kneib +5 · 2 citations
    Computer Science · Mathematics · #Advanced Statistical Methods and Models #Bayesian Methods and Mixture Models #Computation (stat.CO) #FOS: Computer and information sciences #Methodology (stat.ME) #Statistical Methods and Inference
  4. Demystifying Spatial Confounding
    2023/09/28 by Emiko Dupont, Isa Marques, Dupont, Emiko +3 · 3 citations
    Economics, Econometrics and Finance · #Economic and Environmental Valuation #FOS: Computer and information sciences #FOS: Mathematics #Health Systems, Economic Evaluations, Quality of Life #Methodology (stat.ME) #Spatial and Panel Data Analysis #Statistics Theory (math.ST)
  5. Distributional Gradient Boosting Machines
    2022/04/02 by Alexander März, Thomas Kneib, März, Alexander +1 · 2 citations
    Computer Science · #Data Stream Mining Techniques #Explainable Artificial Intelligence (XAI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Data Classification
  6. Gradient boosting in Markov-switching generalized additive models for\n location, scale and shape
    2017/10/06 by Timo Adam, Andreas Mayr, Adam, Timo +3 · 1 citation
    Mathematics · Computer Science · #Statistical Methods and Inference #Bayesian Methods and Mixture Models #Statistical Methods and Bayesian Inference
  7. Conditional Model Selection in Mixed-Effects Models with cAIC4
    2018/03/15 by Säfken, Benjamin, Rügamer, David, Kneib, Thomas +1 · 1 citation
    #Applications (stat.AP) #Computation (stat.CO) #FOS: Computer and information sciences
  8. A Machine Learning and Explainable AI Framework Tailored for Unbalanced Experimental Catalyst Discovery
    2024/07/10 by Parastoo Semnani, Semnani, Parastoo, Mihail Bogojeski +17 · 2 citations
    Decision Sciences · Materials Science · #Chemical Physics (physics.chem-ph) #Data Quality and Management #FOS: Computer and information sciences #FOS: Physical sciences #Machine Learning (cs.LG) #Machine Learning in Materials Science
  9. Probabilistic Topic Modelling with Transformer Representations
    2024/03/06 by Reuter, Arik, Thielmann, Anton, Weisser, Christoph +2 · 1 citation
    #Computation and Language (cs.CL) #FOS: Computer and information sciences #Machine Learning (cs.LG)