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Julian Besag was an outstanding statistical scientist, distinguished for his pioneering work on the statistical theory and analysis of spatial processes, especially conditional lattice systems. His work has been seminal in statistical developments over the last several decades ranging from image analysis to Markov chain Monte Carlo methods. He clarified the role of auto-logistic and auto-normal models as instances of Markov random fields and paved the way for their use in diverse applications. Later work included investigations into the efficacy of nearest neighbour models to accommodate spatial dependence in the analysis of data from agricultural field trials, image restoration from noisy data, and texture generation using lattice models.
Stephen Hawkings contributions to the understanding of gravity, black holes and cosmology were truly immense. They began with the singularity theorems in the 1960s followed by his discovery that black holes have an entropy and consequently a finite t
Donald Lynden-Bells many contributions to astrophysics encompass general relativity, galactic dynamics, telescope design and observational astronomy. In the 1960s, his papers on stellar dynamics led to fundamental insights into the equilibria of elli
Stirling Colgate was a remarkably imaginative physicist, an independent thinker with a wide breadth of interests and contagious enthusiasm, a born leader with enduring drive to attack fundamental problems in science. Among his many achievements, he f
The interpretation of numerical methods, such as finite difference methods for differential equations, as point estimators suggests that formal uncertainty quantification can also be performed in this context. Competing statistical paradigms can be c
On 2010 August 14, a wide-angled coronal mass ejection (CME) was observed. This solar eruption originated from a destabilized filament that connected two active regions and the unwinding of this filament gave the eruption an untwisting motion that dr