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GRASP: NavigatingRetrosyntheticPlanningwith Goal-drivenPolicy

Neural Information Processing Systems

Retrosynthetic planning occupies a crucial position in synthetic chemistry and, accordingly, drug discovery, which aims to find synthetic pathways of a target molecule through a sequential decision-making process on a set of feasible reactions.





A Dataset Card

Neural Information Processing Systems

Table 4 contains the full set of topics for the k " 30 LDA model introduced in 4. Personal 7.96% ive, didnt, thing, bit, thought, week, wanted, started, pretty, id Art 2.70% art, design, de, images, ikea, image, painting, collection, piano, photo 14 C Most Frequent T op-Level Domains Figure 8: Manually labeled images with watermarks and images related to logos or ads. Sentence Image CLIP Similarity Our new service for teams to manage their fleets for racing.



Theory-InspiredPath-RegularizedDifferential NetworkArchitectureSearch(SupplementaryFile)

Neural Information Processing Systems

Next, we also report the average gate activate probability in the normal and reduction cells in Figure 1 (b). At the beginning of the search, we initialize the activation probability of each gate to be one. SameasDARTS, we alternatively update the network parameterW and the architecture parameterβ via gradient descent which is detailed in Algorithm 1. When we compute the gradient βFBtrain(W,β), we ignore the second-order Hessian to accelerate the computation which is the sameasfirst-orderDARTS. For brevity, we usually ignore the notation(k) and i and use X(l) to denote the outputX(l) of any sampleXi ( i = 1,,n) in the l-th layer at any iteration.