Abstract: Discovering molecules (which may be known or may never have been cataloged or ever synthesized) that have desired characteristics is addressed using a machine learning approach. As compared to a brute-force search of a database of known molecules, which may not be computationally feasible, the present machine learning approach renders identification of both known and unknown molecules computationally tractable. Furthermore, the computational effort is largely shifted to training of the machine learning system using a database of known molecules, and the generation of molecules to match any particular characteristics requires relatively little computation. The molecules using the present approach may be further studied, for example, with computer-based simulation or after physical synthesis using biological experimentation to ultimately yield useful chemical compounds.

Abstract: A machine-learning approach jointly generates molecular graphs and corresponding three-dimensional geometries, for example, for searching a chemical space of potential molecules with desired chemical properties. In some examples, molecules are generated incrementally by repeatedly adding atoms to a molecular graph as well as determining geometric (e.g., location) information for the added atoms until a complete molecule is generated. This incremental process can be stochastic enabling random sampling from a chemical space.

Abstract: Discovering molecules (which may be known or may never have been cataloged or ever synthesized) that have desired characteristics is addressed using a machine learning approach. As compared to a brute-force search of a database of known molecules, which may not be computationally feasible, the present machine learning approach renders identification of both known and unknown molecules computationally tractable. Furthermore, the computational effort is largely shifted to training of the machine learning system using a database of known molecules, and the generation of molecules to match any particular characteristics requires relatively little computation. The molecules using the present approach may be further studied, for example, with computer-based simulation or after physical synthesis using biological experimentation to ultimately yield useful chemical compounds.

Abstract: A method and apparatus to determine user identity and limit access to a communications network. A first message containing user identity information is received from a client computer in accordance with a first protocol. A first network address is determined from the first message. A second message containing an information request is also received from the client in accordance with a second protocol, and a second network address is determined from the second message. The requesting user identity is then determined based on the first network address, the user identity information and the second network address. Based on the requesting user identity, it can be decided whether to grant the information request. If access is granted, the requested information is retrieved using the communications network.