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Liam Hodgkinson

  1. Lipschitz Recurrent Neural Networks
    2020/06/22 by N. Benjamin Erichson, Erichson, N. Benjamin, Omri Azencot +7 · 9 citations
    Computer Science · #Anomaly Detection Techniques and Applications #Neural Networks and Applications #Machine Learning in Healthcare
  2. Implicit Langevin Algorithms for Sampling From Log-concave Densities
    2019/03/29 by Liam Hodgkinson, Hodgkinson, Liam, Robert Salomone +3 · 4 citations
    Economics, Econometrics and Finance · Mathematics · #Computation (stat.CO) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Markov Chains and Monte Carlo Methods #Statistical Methods and Inference #Stochastic processes and financial applications
  3. The reproducing Stein kernel approach for post-hoc corrected sampling
    2020/01/25 by Liam Hodgkinson, Robert Salomone, Hodgkinson, Liam +3 · 4 citations
    Computer Science · Engineering · Mathematics · #60B10 (Secondary) #65C05 (Primary) 60J22 #Bayesian Methods and Mixture Models #FOS: Computer and information sciences #FOS: Mathematics #Geophysical Methods and Applications #Machine Learning (stat.ML) #Markov Chains and Monte Carlo Methods #Statistics Theory (math.ST)
  4. Multiplicative noise and heavy tails in stochastic optimization
    2020/06/11 by Liam Hodgkinson, Michael W. Mahoney, Hodgkinson, Liam +1 · 5 citations
    Computer Science · Decision Sciences · #Advanced Bandit Algorithms Research #FOS: Computer and information sciences #FOS: Mathematics #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Optimization and Control (math.OC) #Statistics Theory (math.ST) #Stochastic Gradient Optimization Techniques
  5. Monotonicity and Double Descent in Uncertainty Estimation with Gaussian Processes
    2022/10/14 by Liam Hodgkinson, Hodgkinson, Liam, Chris van der Heide +5 · 2 citations
    Computer Science · Engineering · #FOS: Computer and information sciences #Fault Detection and Control Systems #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Data Classification
  6. The Interpolating Information Criterion for Overparameterized Models
    2023/07/15 by Liam Hodgkinson, Hodgkinson, Liam, Chris van der Heide +7 · 2 citations
    Mathematics · Computer Science · #Statistical Methods and Inference #Bayesian Methods and Mixture Models #Statistical Methods and Bayesian Inference
  7. Generalization Guarantees via Algorithm-dependent Rademacher Complexity
    2023/07/04 by Sarah Sachs, Tim van Erven, Sachs, Sarah +7 · 1 citation
    Computer Science · Engineering · #FOS: Computer and information sciences #Ferroelectric and Negative Capacitance Devices #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Neural Networks and Applications #Stochastic Gradient Optimization Techniques
  8. Stochastic Normalizing Flows
    2020/02/21 by Liam Hodgkinson, Hodgkinson, Liam, Chris van der Heide +5 · 2 citations
    Physics and Astronomy · Computer Science · #Model Reduction and Neural Networks #Gaussian Processes and Bayesian Inference #Generative Adversarial Networks and Image Synthesis
  9. Temperature Optimization for Bayesian Deep Learning
    2024/10/08 by K.C. Ng, Ng, Kenyon, Chris van der Heide +5 · 1 citation
    Computer Science · #Gaussian Processes and Bayesian Inference