David J. C. MacKay
#7,296
Most Influential Person Now
Regius Professor of Engineering at the University of Cambridge
Why Is David J. C. MacKay Influential?
(Suggest an Edit or Addition)According to Wikipedia, Sir David John Cameron MacKay was a British physicist, mathematician, and academic. He was the Regius Professor of Engineering in the Department of Engineering at the University of Cambridge and from 2009 to 2014 was Chief Scientific Advisor to the UK Department of Energy and Climate Change . MacKay wrote the book Sustainable Energy – Without the Hot Air.
David J. C. MacKay's Published Works
Number of citations in a given year to any of this author's works
Total number of citations to an author for the works they published in a given year. This highlights publication of the most important work(s) by the author
Published Works
- Information Theory, Inference, and Learning Algorithms (2004) (9190)
- Bayesian Interpolation (1992) (4200)
- A Practical Bayesian Framework for Backpropagation Networks (1992) (2821)
- Sustainable Energy - Without the Hot Air (2008) (1409)
- Information-Based Objective Functions for Active Data Selection (1992) (1297)
- Turbo Decoding as an Instance of Pearl's "Belief Propagation" Algorithm (1998) (1024)
- Probable networks and plausible predictions - a review of practical Bayesian methods for supervised neural networks (1995) (960)
- The Evidence Framework Applied to Classification Networks (1992) (824)
- Bayesian Online Changepoint Detection (2007) (638)
- The Role of Constraints in Hebbian Learning (1994) (473)
- Elliptical slice sampling (2009) (417)
- Introduction to Gaussian processes (1998) (408)
- A Revolution: Belief Propagation in Graphs with Cycles (1997) (387)
- Introduction to Monte Carlo Methods (1998) (385)
- MCMC for Doubly-intractable Distributions (2006) (381)
- Bayesian methods for adaptive models (1992) (378)
- A hierarchical Dirichlet language model (1995) (337)
- Comparison of Approximate Methods for Handling Hyperparameters (1999) (291)
- BAYESIAN NON-LINEAR MODELING FOR THE PREDICTION COMPETITION (1996) (288)
- Bayesian Methods for Backpropagation Networks (1996) (274)
- A Practical Bayesian Framework for Backprop Networks (1991) (263)
- Variational Gaussian process classifiers (2000) (242)
- Bayesian Methods for Mixtures of Experts (1995) (232)
- Tractable nonparametric Bayesian inference in Poisson processes with Gaussian process intensities (2009) (232)
- Ensemble Learning for Blind Image Separation and Deconvolution (2000) (202)
- Gaussian Process Robust Regression for Noisy Heart Rate Data (2008) (198)
- Bayesian neural networks and density networks (1995) (179)
- Gaussian Processes - A Replacement for Supervised Neural Networks? (1997) (146)
- Developments in Probabilistic Modelling with Neural Networks - Ensemble Learning (1995) (130)
- Choice of Basis for Laplace Approximation (1998) (129)
- Independent component analysis of microarray data in the study of endometrial cancer (2004) (107)
- HYPERPARAMETERS: OPTIMIZE, OR INTEGRATE OUT? (1996) (107)
- Estimation of the amount of retained austenite in austempered ductile irons using neural networks (2001) (103)
- Predicting and understanding the stability of G-quadruplexes (2009) (102)
- Unsupervised Classifiers, Mutual Information and 'Phantom Targets' (1991) (95)
- A restatement of the natural science evidence base concerning the health effects of low-level ionizing radiation (2017) (93)
- Impact toughness of C-Mn steel arc welds : Bayesian neural network analysis (1995) (93)
- Bayesian Model Comparison and Backprop Nets (1991) (91)
- Bayesian Neural Network Analysis of Fatigue Crack Growth Rate in Nickel Base Superalloys (1996) (87)
- A decomposition model to track gene expression signatures: preview on observer-independent classification of ovarian cancer (2002) (83)
- Independent Component Analysis: Ensemble Learning for blind source separation (2001) (81)
- Neural network model of creep strength of austenitic stainless steels (2002) (78)
- Solar energy in the context of energy use, energy transportation and energy storage (2013) (72)
- The yield and ultimate tensile strength of steel welds (1997) (71)
- The Gaussian Process Density Sampler (2008) (69)
- A recurrent neural network for modelling dynamical systems. (1998) (64)
- Bayesian neural network model for austenite formation in steels (1996) (61)
- Price carbon — I will if you will (2015) (61)
- Design of a creep resistant nickel base superalloy for power plant applications: Part 1 - Mechanical properties modelling (2003) (60)
- Analysis of Linsker's application of Hebbian rules to linear networks (1990) (58)
- Analysis of Linsker's Simulations of Hebbian Rules (1990) (57)
- Theoretical design of ferritic creep resistant steels using neural network, kinetic, and thermodynamic models (1999) (43)
- Estimation of Hot Torsion Stress Strain Curves in Iron Alloys Using a Neural Network Analysis (1999) (42)
- Gaussian process modelling of austenite formation in steel (1999) (40)
- Eye tracking off the shelf (2004) (36)
- Tensile properties of mechanically alloyed oxide dispersion strengthened iron alloys Part 1 - Neural networkmodels (1998) (35)
- Modelling Uncertainty in the Game of Go (2004) (34)
- Speech dasher: fast writing using speech and gaze (2010) (31)
- Failures of the One-Step Learning Algorithm (2001) (31)
- Bayesian methods for supervised neural networks (1998) (29)
- Estimation of the γ and γ' lattice parameters in nickel-base superalloys using neural network analysis (1998) (29)
- Nested sampling for Potts models (2005) (29)
- Global Carbon Pricing: The Path to Climate Cooperation (2017) (27)
- Modelling creep rupture strength of ferritic steel welds (2000) (27)
- Bayesian Non-Linear Modelling with Neural Networks (1995) (25)
- Density networks (2000) (24)
- Comparison of artificial neural networks with gaussian processes to model the yield strength of nickel-base superalloys (1999) (24)
- Fast and Flexible Selection with a Single Switch (2009) (24)
- Could energy-intensive industries be powered by carbon-free electricity? (2013) (24)
- Information Theory, Pattern Recognition and Neural Networks (1997) (21)
- Reproducibility Assessment of Independent Component Analysis of Expression Ratios From DNA Microarrays (2003) (19)
- Equivalence of Linear Boltzmann Chains and Hidden Markov Models (1996) (19)
- Maximum Entropy Connections: Neural Networks (1991) (18)
- Model for solidification cracking in low alloy steel weld metals (1996) (17)
- PREDICTION OF DEFORMED AND ANNEALED MICROSTRUCTURES USING BAYESIAN NEURAL NETWORKS AND GAUSSIAN PROCESSES (1997) (17)
- Interpolation models with multiple hyperparameters (1998) (15)
- Model fitting as an aid to bridge balancing in neuronal recording (2001) (13)
- Ergodic pumping: A mechanism to drive biomolecular conformation changes (2006) (11)
- Nonparametric Bayesian Density Modeling with Gaussian Processes (2009) (11)
- The Nonnegative Boltzmann Machine (1999) (11)
- Density Networks and their Application to Protein Modelling (1996) (9)
- Design of New Creep-Resistant Nickel-Base Superalloys for Power-Plant Applications (1999) (7)
- Rate of Information Acquisition by a Species Subjected to Natural Selection (1999) (5)
- Improving PPM with Dynamic Parameter Updates (2015) (4)
- Neural Network Image Deconvolution (1996) (4)
- The Evidence for Neural Networks (1992) (3)
- Bayesian Comparison of Models for Images (1996) (2)
- Consistency of The Mortality of Chronically-irradiated Beagles with the Linear No-Threshold Model (2014) (2)
- Independent Component Analysis of Microarray Data in the Study of Endometrial Cancer ( Brief Title : Independent Component Analysis for Gene Arrays ) (2003) (2)
- Bayesian Analysis of Linear Phased-Array Radar (1996) (2)
- Static and Dynamic Modelling of Materials Forging (2001) (2)
- Neural Network Image (1996) (2)
- Information theory, inference, and learning algoritms / David J.C. MacKay (2003) (2)
- Simple Proofs of a Rectangle Tiling Theorem (2009) (1)
- Speech dasher: a demonstration of text input using speech and approximate pointing (2014) (1)
- Solution of a Toy Problem by Reinforcement Learning (2006) (1)
- Is the Pope the Pope? (1996) (1)
- The spatial arrangement of cones in the fovea : Bayesian analysis (1993) (0)
- Density Networks with Application to Protein Modelling Statement regarding Originality of Thesis (1998) (0)
- The Secret of Weight Management Or Why you Weigh More on Thick Carpet (2002) (0)
- UNIVERSITY OF CAMBRIDGE PROGRAMME FOR INDUSTRY Neural Networks Summer School Bayesian Methods for Neural Networks: Theory and Applications (1995) (0)
- Sustainable materials with both eyes open (2012) (0)
- Estimation of the y and y' Lattice Superalloys Using Neural Network Parameters in Nickel-base Analysis (2001) (0)
- Appendix A A restatement of the natural science evidence base concerning the health effects of low-level ionizing radiation Proceedings of the Royal Society B DOI 10.1098/rspb.2017-1070 (2017) (0)
- The Stability of Human Colour Memory and Distribution of Recalled Colours (2006) (0)
- Bayesian Neural Network Model for Estimation of Weld Properties (2001) (0)
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What Schools Are Affiliated With David J. C. MacKay?
David J. C. MacKay is affiliated with the following schools:
