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    SYNTHETIC DATA FOR FIBER SENSING TASKS WITH CONTROLLABLE GENERATION AND DIFFERENTIABLE INFERENCE
    21.
    发明申请
    SYNTHETIC DATA FOR FIBER SENSING TASKS WITH CONTROLLABLE GENERATION AND DIFFERENTIABLE INFERENCE 有权

    公开(公告)号：US20250148281A1

    公开(公告)日：2025-05-08

    申请号：US18909467

    申请日：2024-10-08

    Applicant: NEC Laboratories America, Inc.

    Inventor： Shaobo Han ,  Tingfeng Li ,  Renqiang Min

    IPC: G06N3/08

    Abstract: Systems and methods include collecting real-world distributed-optic fiber sensing (DFOS) sensing data from a target environment as a reference dataset. A synthetic sketch dataset is constructed as a parameterized computer program. A synthetic waterfall is generated from a deep neural network as an image translator from the sketch waterfall with nonlinear distortions and background noises added. Parameters are optimized for generating the synthetic waterfall under a loss function where the loss function encodes a generalization performance on the real-world dataset and encodes granularities from a sensing process and uncontrollable factors.

    LANGUAGE MODELS WITH DYNAMIC OUTPUTS
    22.
    发明申请
    LANGUAGE MODELS WITH DYNAMIC OUTPUTS 有权

    公开(公告)号：US20250053774A1

    公开(公告)日：2025-02-13

    申请号：US18776926

    申请日：2024-07-18

    Applicant: NEC Laboratories America, Inc.

    Inventor： Christopher Malon ,  Christopher A White ,  Renqiang Min ,  Iain Melvin

    IPC: G06N3/006 ,  G06N3/092 ,  G06N5/04 ,  G16H50/70

    Abstract: Methods and systems for answering a query include generating first tokens in response to an input query using a language model, the first tokens including a retrieval rule. A retrieval rule is used to search for information to generate dynamic tokens. The retrieval rule in the first tokens is replaced with the dynamic tokens to generate a dynamic partial response. Second tokens are generated in response to the input query. The second tokens are appended to the dynamic partial response to generate an output responsive to the input query.

    PEPTIDE SEARCH SYSTEM FOR IMMUNOTHERAPY
    25.
    发明公开
    PEPTIDE SEARCH SYSTEM FOR IMMUNOTHERAPY 审中-公开

    公开(公告)号：US20240071572A1

    公开(公告)日：2024-02-29

    申请号：US18471667

    申请日：2023-09-21

    Applicant: NEC Laboratories America, Inc.

    Inventor： Renqiang Min ,  Hans Peter Graf ,  Ziqi Chen

    IPC: G16B40/00 ,  G06N3/08 ,  G16B15/30

    CPC classification number: G16B40/00 ,  G06N3/08 ,  G16B15/30

    Abstract: A system for binding peptide search for immunotherapy is presented. The system includes employing a deep neural network to predict a peptide presentation given Major Histocompatibility Complex allele sequences and peptide sequences, training a Variational Autoencoder (VAE) to reconstruct peptides by converting the peptide sequences into continuous embedding vectors, running a Monte Carlo Tree Search to generate a first set of positive peptide vaccine candidates, running a Bayesian Optimization search with the trained VAE and a Backpropagation search with the trained VAE to generate a second set of positive peptide vaccine candidates, using a sampling from a Position Weight Matrix (sPWM) to generate a third set of positive peptide vaccine candidates, screening and merging the first, second, and third sets of positive peptide vaccine candidates, and outputting qualified peptides for immunotherapy from the screened and merged sets of positive peptide vaccine candidates.

    FEW-SHOT VIDEO CLASSIFICATION
    26.
    发明公开
    FEW-SHOT VIDEO CLASSIFICATION 审中-公开

    公开(公告)号：US20240054782A1

    公开(公告)日：2024-02-15

    申请号：US18366931

    申请日：2023-08-08

    Applicant: NEC Laboratories America, Inc.

    Inventor： Kai Li ,  Renqiang Min ,  Haifeng Xia

    IPC: G06V20/40 ,  G06V10/774

    CPC classification number: G06V20/41 ,  G06V20/46 ,  G06V10/774 ,  G06V20/48

    Abstract: Methods and systems for video processing include enriching an input video feature from an input video frame set using a meta-action bank video sub-actions to generate enriched features. Reinforced image representation is performed using reinforcement learning to compare support image frames and query image frames and determine an importance of the input video frame. A classification is performed on the input video frame based on the importance and the enriched features to generate a label. An action is performed responsive to the generated label.

    PEPTIDE MUTATION POLICIES FOR TARGETED IMMUNOTHERAPY
    28.
    发明申请
    PEPTIDE MUTATION POLICIES FOR TARGETED IMMUNOTHERAPY 有权

    公开(公告)号：US20220327425A1

    公开(公告)日：2022-10-13

    申请号：US17711658

    申请日：2022-04-01

    Applicant: NEC Laboratories America, Inc.

    Inventor： Renqiang Min ,  Hans Peter Graf ,  Ligong Han

    IPC: G06N20/00

    Abstract: Methods and systems for training a machine learning model include embedding a state, including a peptide sequence and a protein, as a vector. An action, including a modification to an amino acid in the peptide sequence, is predicted using a presentation score of the peptide sequence by the protein as a reward. A mutation policy model is trained, using the state and the reward, to generate modifications that increase the presentation score.

    Multi-scale text filter conditioned generative adversarial networks
    29.
    发明授权
    Multi-scale text filter conditioned generative adversarial networks 有权

    公开(公告)号：US11170256B2

    公开(公告)日：2021-11-09

    申请号：US16577337

    申请日：2019-09-20

    Applicant: NEC Laboratories America, Inc.

    Inventor： Renqiang Min ,  Bing Bai ,  Yogesh Balaji

    IPC: G06K9/00 ,  G06K9/62 ,  G06N3/08 ,  G06N3/04 ,  G06F40/279

    Abstract: Systems and methods for processing video are provided. The method includes receiving a text-based description of active scenes and representing the text-based description as a word embedding matrix. The method includes using a text encoder implemented by neural network to output frame level textual representation and video level representation of the word embedding matrix. The method also includes generating, by a shared generator, frame by frame video based on the frame level textual representation, the video level representation and noise vectors. A frame level and a video level convolutional filter of a video discriminator are generated to classify frames and video of the frame by frame video as true or false. The method also includes training a conditional video generator that includes the text encoder, the video discriminator, and the shared generator in a generative adversarial network to convergence.

    DETECTING ADVERSARIAL EXAMPLES
    30.
    发明申请
    DETECTING ADVERSARIAL EXAMPLES 审中-公开

    公开(公告)号：US20200250304A1

    公开(公告)日：2020-08-06

    申请号：US16778213

    申请日：2020-01-31

    Applicant: NEC Laboratories America, Inc.

    Inventor： Erik Kruus ,  Renqiang Min ,  Yao Li

    IPC: G06F21/55 ,  G06N3/08 ,  G06N3/04

    Abstract: Systems and methods for detecting adversarial examples are provided. The method includes generating encoder direct output by projecting, via an encoder, input data items to a low-dimensional embedding vector of reduced dimensionality with respect to the one or more input data items to form a low-dimensional embedding space. The method includes regularizing the low-dimensional embedding space via a training procedure such that the input data items produce embedding space vectors whose global distribution is expected to follow a simple prior distribution. The method also includes identifying whether each of the input data items is an adversarial or unnatural input. The method further includes classifying, during the training procedure, those input data items which have not been identified as adversarial or unnatural into one of multiple classes.

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