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Loaiza-Ganem, Gabriel

  1. CaloMan: Fast generation of calorimeter showers with density estimation on learned manifolds
    2022/11/23 by Cresswell, Jesse C., Ross, Brendan Leigh, Loaiza-Ganem, Gabriel +3 · 10 citations
    #Data Analysis #FOS: Computer and information sciences #FOS: Physical sciences #High Energy Physics - Experiment (hep-ex) #High Energy Physics - Phenomenology (hep-ph) #Instrumentation and Detectors (physics.ins-det) #Machine Learning (cs.LG) #Statistics and Probability (physics.data-an)
  2. Verifying the Union of Manifolds Hypothesis for Image Data
    2022/07/06 by Bradley C. A. Brown, Anthony L. Caterini, Brown, Bradley C. A. +7 · 9 citations
    Biochemistry, Genetics and Molecular Biology · Computer Science · #Artificial Intelligence (cs.AI) #Cell Image Analysis Techniques #FOS: Computer and information sciences #Generative Adversarial Networks and Image Synthesis #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Single-cell and spatial transcriptomics
  3. CaloChallenge 2022: A Community Challenge for Fast Calorimeter Simulation
    2024/10/28 by Krause, Claudius, Giannelli, Michele Faucci, Kasieczka, Gregor +66 · 21 citations
    #FOS: Computer and information sciences #FOS: Physical sciences #High Energy Physics - Experiment (hep-ex) #High Energy Physics - Phenomenology (hep-ph) #Instrumentation and Detectors (physics.ins-det) #Machine Learning (cs.LG)
  4. Deep Generative Models through the Lens of the Manifold Hypothesis: A Survey and New Connections
    2024/04/03 by Gabriel Loaiza-Ganem, Loaiza-Ganem, Gabriel, Brendan Leigh Ross +7 · 9 citations
    Computer Science · #Artificial Intelligence (cs.AI) #Cellular Automata and Applications #FOS: Computer and information sciences #Generative Adversarial Networks and Image Synthesis #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  5. A Geometric Framework for Understanding Memorization in Generative Models
    2024/10/31 by Brendan Leigh Ross, Hamidreza Kamkari, Ross, Brendan Leigh +13 · 2 voices · 6 citations
    #stat.ML #cs.LG
  6. Rectangular Flows for Manifold Learning
    2021/06/02 by Caterini, Anthony L., Loaiza-Ganem, Gabriel, Pleiss, Geoff +1 · 3 citations
    #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  7. A Geometric View of Data Complexity: Efficient Local Intrinsic Dimension Estimation with Diffusion Models
    2024/06/05 by Hamidreza Kamkari, Kamkari, Hamidreza, Brendan Leigh Ross +7 · 5 citations
    Computer Science · Mathematics · #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Statistical Methods and Inference #Topological and Geometric Data Analysis
  8. Relating Regularization and Generalization through the Intrinsic Dimension of Activations
    2022/11/23 by Brown, Bradley C. A., Juravsky, Jordan, Caterini, Anthony L. +1 · 2 citations
    #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Machine Learning (cs.LG)
  9. Maximum Entropy Flow Networks
    2017/01/12 by Loaiza-Ganem, Gabriel, Gao, Yuanjun, Cunningham, John P. · 1 citation
    #FOS: Computer and information sciences #Machine Learning (stat.ML) #Methodology (stat.ME)
  10. Data-Efficient Multimodal Fusion on a Single GPU
    2023/12/15 by Vouitsis, Noël, Liu, Zhaoyan, Gorti, Satya Krishna +5 · 2 citations
    #Artificial Intelligence (cs.AI) #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Machine Learning (cs.LG)
  11. The continuous Bernoulli: fixing a pervasive error in variational autoencoders
    2019/07/16 by Gabriel Loaiza-Ganem, Loaiza-Ganem, Gabriel, John P. Cunningham +1 · 1 citation
    Computer Science · Physics and Astronomy · #FOS: Computer and information sciences #Generative Adversarial Networks and Image Synthesis #Image and Signal Denoising Methods #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Model Reduction and Neural Networks
  12. The continuous categorical: a novel simplex-valued exponential family
    2020/02/20 by Elliott Gordon-Rodríguez, Gabriel Loaiza-Ganem, Gordon-Rodriguez, Elliott +3 · 1 citation
    Computer Science · Mathematics · #Bayesian Methods and Mixture Models #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Markov Chains and Monte Carlo Methods
  13. Bayesian Nonparametrics for Offline Skill Discovery
    2022/02/09 by Villecroze, Valentin, Braviner, Harry J., Naderian, Panteha +2 · 1 citation
    #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  14. Diagnosing and Fixing Manifold Overfitting in Deep Generative Models
    2022/04/14 by Loaiza-Ganem, Gabriel, Ross, Brendan Leigh, Cresswell, Jesse C. +1 · 1 citation
    #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Methodology (stat.ME)
  15. Neural Implicit Manifold Learning for Topology-Aware Density Estimation
    2022/06/22 by Ross, Brendan Leigh, Loaiza-Ganem, Gabriel, Caterini, Anthony L. +1 · 1 citation
    #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  16. TR0N: Translator Networks for 0-Shot Plug-and-Play Conditional Generation
    2023/04/26 by Liu, Zhaoyan, Vouitsis, Noel, Gorti, Satya Krishna +2 · 1 citation
    #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  17. Deep Ensembles Secretly Perform Empirical Bayes
    2025/01/29 by Loaiza-Ganem, Gabriel, Villecroze, Valentin, Wang, Yixin · 2 citations
    #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  18. A Geometric Explanation of the Likelihood OOD Detection Paradox
    2024/03/27 by Kamkari, Hamidreza, Ross, Brendan Leigh, Cresswell, Jesse C. +3 · 1 citation
    #Artificial Intelligence (cs.AI) #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  19. Textual Bayes: Quantifying Uncertainty in LLM-Based Systems
    2025/06/11 by Ross, Brendan Leigh, Vouitsis, Noël, Ghomi, Atiyeh Ashari +8 · 3 citations
    #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  20. Last Layer Empirical Bayes
    2025/05/21 by Villecroze, Valentin, Wang, Yixin, Loaiza-Ganem, Gabriel · 1 citation
    #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)