Hodgkinson, Liam
- Lipschitz Recurrent Neural Networks
2020/06/22 by N. Benjamin Erichson, Omri Azencot, Erichson, N. Benjamin +7 · 8 citations
Computer Science · #Anomaly Detection Techniques and Applications #Neural Networks and Applications #Machine Learning in Healthcare
- The reproducing Stein kernel approach for post-hoc corrected sampling
2020/01/25 by Hodgkinson, Liam, Salomone, Robert, Roosta, Fred · 3 citations
#60B10 (Secondary) #65C05 (Primary) 60J22 #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (stat.ML) #Statistics Theory (math.ST)
- Implicit Langevin Algorithms for Sampling From Log-concave Densities
2019/03/29 by Liam Hodgkinson, Robert Salomone, Hodgkinson, Liam +3 · 2 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
- Fat-Tailed Variational Inference with Anisotropic Tail Adaptive Flows
2022/05/16 by Liang, Feynman, Hodgkinson, Liam, Mahoney, Michael W. · 2 citations
#FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
- When are ensembles really effective?
2023/05/21 by Theisen, Ryan, Kim, Hyunsuk, Yang, Yaoqing +2 · 2 citations
#FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
- Multiplicative noise and heavy tails in stochastic optimization
2020/06/11 by Liam Hodgkinson, Hodgkinson, Liam, Michael W. Mahoney +1 · 2 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
- Monotonicity and Double Descent in Uncertainty Estimation with Gaussian Processes
2022/10/14 by Hodgkinson, Liam, van der Heide, Chris, Roosta, Fred +1 · 2 citations
#FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
- The Interpolating Information Criterion for Overparameterized Models
2023/07/15 by Liam Hodgkinson, Chris van der Heide, Hodgkinson, Liam +7 · 2 citations
Mathematics · Computer Science · #Statistical Methods and Inference #Bayesian Methods and Mixture Models #Statistical Methods and Bayesian Inference
- 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
- Temperature Optimization for Bayesian Deep Learning
2024/10/08 by K.C. Ng, Chris van der Heide, Ng, Kenyon +5 · 1 citation
Computer Science · #Gaussian Processes and Bayesian Inference