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2 High-throughput Data and New Representations for Models and Machine Learning Gus L. W. Hart
3 Why am I here? Automatic-FLOW for Materials Discovery
4 This talk is for you, not for me Automatic-FLOW for Materials Discovery
5 High-Throughput Alloy Search Experimental Structures (ICSD) Automatic-FLOW for Materials Discovery
6 High-Throughput Alloy Search Experimental Structures (ICSD) Automatic-FLOW for Materials Discovery
7 High-Throughput Alloy Search Experimental Structures (ICSD) Automatic-FLOW for Materials Discovery
8 High-Throughput Alloy Search Experimental Structures (ICSD) Combinatorial Substitution Automatic-FLOW for Materials Discovery
9 High-Throughput Alloy Search Experimental Structures (ICSD) Combinatorial Substitution Automatic-FLOW for Materials Discovery
10 High-Throughput Alloy Search Experimental Structures (ICSD) Combinatorial Substitution Automatic-FLOW for Materials Discovery
11 High-Throughput Alloy Search Experimental Structures (ICSD) Combinatorial Substitution Automatic-FLOW for Materials Discovery
12 High-Throughput Alloy Search Experimental Structures (ICSD) Combinatorial Substitution Automatic-FLOW for Materials Discovery
13 An Application: 153 Platinum-Group Alloys Gus L. W. Hart, Stefano Curtarolo, Thaddeus B. Massalski, Ohad Levy; Phys. Rev. X, (Dec ). (msg.byu.edu/pubs.php) cutout from viewpoint
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17 But I want to explore a larger space...and go to finite T...
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23 The phenomenon is entirely one of the configuration of atoms on a fixed lattice.
24 The phenomenon is entirely one of the configuration of atoms on a fixed lattice.
25 Automatic-FLOW for Materials Discovery
26 Representation is rotationally, translationally, permutationally invariant Automatic-FLOW for Materials Discovery
27 Genetic Algorithm for Model Building
28 Solving an under-determined problem
29 Solving an under-determined problem
30 Solving an under-determined problem
31 Solving an under-determined problem
32 Solving an under-determined problem
33 Practicality of CS: norm techniques
34 Practicality of CS: norm techniques
35 Practicality of CS: norm techniques CS is practical because there are so many good numerical approaches for enforcing the norm
36 Practicality of CS: norm techniques CS is practical because there are so many good numerical approaches for enforcing the norm
37 Practicality of CS: norm techniques CS is practical because there are so many good numerical approaches for enforcing the norm
38 Practicality of CS: norm techniques CS is practical because there are so many good numerical approaches for enforcing the norm
39 Practicality of CS: norm techniques CS is practical because there are so many good numerical approaches for enforcing the norm
40 Practicality of CS: norm techniques CS is practical because there are so many good numerical approaches for enforcing the norm
41 Practicality of CS: norm techniques CS is practical because there are so many good numerical approaches for enforcing the norm
42 Practicality of CS: norm techniques CS is practical because there are so many good numerical approaches for enforcing the norm
43 Practicality of CS: norm techniques CS is practical because there are so many good numerical approaches for enforcing the 3 2 norm min `1 norm min `2 norm
44 Bayesian Compressive Sensing vs. GA FIG. 7. Comparison between re-weighted Bayesian cluster expansion model for the binary systems Ag-P 17
45 Bayesian Compressive Sensing vs. GA days seconds FIG. 7. Comparison between re-weighted Bayesian cluster expansion model for the binary systems Ag-P 17
46 Bayesian Compressive Sensing vs. GA FIG. 7. Comparison between re-weighted Bayes cluster expansion model for the binary systems Ag BCS results and the 18 solid curves indicate GA resu
47 Bayesian Compressive Sensing Stand-alone Solver
48 But I want to explore a much larger space...and go to finite T...
49 But I want to explore a much larger space...and go to finite T... I d like to go off the lattice...
50 But compressive sensing uncovered DFT problems
51 Remember the rectangle rule from calculus? Automatic-FLOW for Materials Discovery
52 Remember the rectangle rule from calculus? Z 1 0 (x 1/2) 2 dx Automatic-FLOW for Materials Discovery
53 Remember the rectangle rule from calculus? 0.25 Z (x 1/2) 2 dx Automatic-FLOW for Materials Discovery
54 Remember the rectangle rule from calculus? 0.25 Z (x 1/2) 2 dx Relative Error Number of rectangles Automatic-FLOW for Materials Discovery
55 Remember the rectangle rule from calculus? 0.25 Z (x 1/2) 2 dx Relative Error Number of rectangles Automatic-FLOW for Materials Discovery
56 Remember the rectangle rule from calculus? 0.25 Z (x 1/2) 2 dx Relative Error Number of rectangles Automatic-FLOW for Materials Discovery
57 Remember the rectangle rule from calculus? 0.25 Z (x 1/2) 2 dx Relative Error Number of rectangles Relative Error Number of rectangles Automatic-FLOW for Materials Discovery
58 Remember the rectangle rule from calculus? 0.25 Z (x 1/2) 2 dx Relative Error Automatic-FLOW for Materials Discovery Number of rectangles
59 Remember the rectangle rule from calculus? 0.25 Z (x 1/2) 2 dx Automatic-FLOW for Materials Discovery Relative Error Numerical Integration of Periodic Functions: A 10 Few -29 Examples, J. A. C. Weideman,The American Mathematical Monthly, (Jan., ), pp Number of rectangles
60 1976: Teton Dam Disaster and MK Paper Automatic-FLOW Thursday, February 26, 15 for Materials Discovery
61 1976: Teton Dam Disaster and MK Paper Automatic-FLOW Thursday, February 26, 15 for Materials Discovery
62 1976: Teton Dam Disaster and MK Paper Automatic-FLOW Thursday, February 26, 15 for Materials Discovery
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