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of 33
pro vyhledávání: '"Hong, Haokai"'
This paper proposes a new 3D molecule generation framework, called GOAT, for fast and effective 3D molecule generation based on the flow-matching optimal transport objective. Specifically, we formulate a geometric transport formula for measuring the
Externí odkaz:
http://arxiv.org/abs/2405.15252
Can we train a molecule generator that can generate 3D molecules from a new domain, circumventing the need to collect data? This problem can be cast as the problem of domain adaptive molecule generation. This work presents a novel and principled diff
Externí odkaz:
http://arxiv.org/abs/2404.00962
Autor:
Hong, Haokai, Jiang, Min
Multi-objective optimization problems (MOPs) necessitate the simultaneous optimization of multiple objectives. Numerous studies have demonstrated that evolutionary computation is a promising paradigm for solving complex MOPs, which involve optimizati
Externí odkaz:
http://arxiv.org/abs/2312.06125
The large-scale multiobjective optimization problem (LSMOP) is characterized by simultaneously optimizing multiple conflicting objectives and involving hundreds of decision variables. Many real-world applications in engineering fields can be modeled
Externí odkaz:
http://arxiv.org/abs/2304.04071
We define very large-scale multiobjective optimization problems as optimizing multiple objectives (VLSMOPs) with more than 100,000 decision variables. These problems hold substantial significance, given the ubiquity of real-world scenarios necessitat
Externí odkaz:
http://arxiv.org/abs/2304.04067
Large-scale multiobjective optimization problems (LSMOPs) refer to optimization problems with multiple conflicting optimization objectives and hundreds or even thousands of decision variables. A key point in solving LSMOPs is how to balance explorati
Externí odkaz:
http://arxiv.org/abs/2205.10052
The main feature of large-scale multi-objective optimization problems (LSMOP) is to optimize multiple conflicting objectives while considering thousands of decision variables at the same time. An efficient LSMOP algorithm should have the ability to e
Externí odkaz:
http://arxiv.org/abs/2108.04197
Publikováno v:
In Information Sciences June 2024 670
Large-scale multiobjective optimization problems (LSMOPs) are characterized as involving hundreds or even thousands of decision variables and multiple conflicting objectives. An excellent algorithm for solving LSMOPs should find Pareto-optimal soluti
Externí odkaz:
http://arxiv.org/abs/2101.02932
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