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6 Nov 2019: uj = Φ1(tj) = erf. 1(. tj. α. 2. ),. where tjs are drawn randomly from the uniform distribution U([0, 1]). ... Let us discretise theinterval [0, 1] by points tj = j/N and write uj = f(tj).

2 Dec 2021: i. {avgj. ([Re(tj) RΞi (gtj)]. 2)}. i. , (S2). where i iterates over all datasets and j over all pointswithin the experimental dataset Re(tj) = Re(tj)/Re(0)enumerated by ... avgj. ([Re(tj) RΞ (gntj)]2. ). (S3). Here, all minimizations were performed

24 Nov 2006: K} such that. ti º tj , j = 1, 2,. , ... K. If ti tj for all j 6= i, we let (ti, ti1,. ,

16 Feb 2021: CAN STABLE AND ACCURATE NEURAL NETWORKS BE COMPUTED? – ON THEBARRIERS OF DEEP LEARNING AND SMALE’S 18TH PROBLEM. VEGARD ANTUN, MATTHEW J. COLBROOK†, AND ANDERS C. HANSEN†. ABSTRACT. Deep learning (DL) has had unprecedented success and is now

2 Sep 2012: FL43CH26-Koch ARI 15 November 2010 14:32. Collective Hydrodynamics ofSwimming Microorganisms:Living FluidsDonald L. Koch1 and Ganesh Subramanian21 School of Chemical and Biomolecular Engineering, Cornell University, Ithaca,New York 14853; email:

9 May 2019: Computational Projects. Lecture 5: Gaussian Elimination / LU decomposition. http://www.maths.cam.ac.uk/undergrad/catam/part-ia-lectures. Dr Rob Jack, DAMTP. 1. Motivation. So far we considered algorithms that correspond to very short MATLAB programs,

5 May 2020: Computational Projects. Lecture 6: Improving LU decomposition. http://www.maths.cam.ac.uk/undergrad/catam/part-ia-lectures. Dr Rob Jack, DAMTP. Recall. Suppose we want to solve Ax = b with. A =. 0 11 0. , b =. 23. <latexit

4 Feb 2022: 0/34. The finite-dimensional case. du. dt= Au, A Cnn, u(0) = u0 Cn u(t) = exp(tA)u0 =. j=0. tj. j!Aju0. E.g., if A = PDP1, with

1 Dec 2021: 0/34. The finite-dimensional case. du. dt= Au, A Cnn, u(0) = u0 Cn u(t) = exp(tA)u0 =. j=0. tj. j!Aju0. E.g., if A = PDP1, D =

1 Sep 2011: More details on the problems relevant to k;p can befound in [1],[2],[5].Recall that Nj(t) := (tjk tj) [tj; tj1; : : :; tjk] ( t)k1+ ;so that suppNj = (tj; tjk); ... degree p such thatsuppMj;p = (tj; tjp1); Z tjp1tj Mj;p(x)dx = 1;and by!