Search

David Robert Vincent

Examiner (ID: 2459)

Most Active Art Unit
2123
Art Unit(s)
2123, 2129, 2615, 2732, 2713, 2787, 2661, 2124, 2731, 3628
Total Applications
1744
Issued Applications
1408
Pending Applications
132
Abandoned Applications
219

Applications

Application numberTitle of the applicationFiling DateStatus
Array ( [id] => 16527790 [patent_doc_number] => 20200401870 [patent_country] => US [patent_kind] => A1 [patent_issue_date] => 2020-12-24 [patent_title] => SYSTEM AND METHOD FOR DESIGNING EFFICIENT SUPER RESOLUTION DEEP CONVOLUTIONAL NEURAL NETWORKS BY CASCADE NETWORK TRAINING, CASCADE NETWORK TRIMMING, AND DILATED CONVOLUTIONS [patent_app_type] => utility [patent_app_number] => 17/007739 [patent_app_country] => US [patent_app_date] => 2020-08-31 [patent_effective_date] => 0000-00-00 [patent_drawing_sheets_cnt] => 0 [patent_figures_cnt] => 0 [patent_no_of_words] => 8924 [patent_no_of_claims] => 0 [patent_no_of_ind_claims] => -21 [patent_words_short_claim] => 49 [patent_maintenance] => 1 [patent_no_of_assignments] => 0 [patent_current_assignee] =>[type] => publication [pdf_file] =>[firstpage_image] =>[orig_patent_app_number] => 17007739 [rel_patent_id] =>[rel_patent_doc_number] =>)
17/007739
System and method for designing efficient super resolution deep convolutional neural networks by cascade network training, cascade network trimming, and dilated convolutions Aug 30, 2020 Issued
Array ( [id] => 16659739 [patent_doc_number] => 20210056376 [patent_country] => US [patent_kind] => A1 [patent_issue_date] => 2021-02-25 [patent_title] => TRAINING MACHINE LEARNING MODELS FOR AUTOMATED COMPOSITION GENERATION [patent_app_type] => utility [patent_app_number] => 16/998583 [patent_app_country] => US [patent_app_date] => 2020-08-20 [patent_effective_date] => 0000-00-00 [patent_drawing_sheets_cnt] => 0 [patent_figures_cnt] => 0 [patent_no_of_words] => 23769 [patent_no_of_claims] => 0 [patent_no_of_ind_claims] => -17 [patent_words_short_claim] => 73 [patent_maintenance] => 1 [patent_no_of_assignments] => 0 [patent_current_assignee] =>[type] => publication [pdf_file] =>[firstpage_image] =>[orig_patent_app_number] => 16998583 [rel_patent_id] =>[rel_patent_doc_number] =>)
16/998583
TRAINING MACHINE LEARNING MODELS FOR AUTOMATED COMPOSITION GENERATION Aug 19, 2020 Abandoned
Array ( [id] => 18703724 [patent_doc_number] => 11790238 [patent_country] => US [patent_kind] => B2 [patent_issue_date] => 2023-10-17 [patent_title] => Multi-task neural networks with task-specific paths [patent_app_type] => utility [patent_app_number] => 16/995655 [patent_app_country] => US [patent_app_date] => 2020-08-17 [patent_effective_date] => 0000-00-00 [patent_drawing_sheets_cnt] => 6 [patent_figures_cnt] => 6 [patent_no_of_words] => 10259 [patent_no_of_claims] => 20 [patent_no_of_ind_claims] => 3 [patent_words_short_claim] => 304 [patent_maintenance] => 1 [patent_no_of_assignments] => 0 [patent_current_assignee] =>[type] => patent [pdf_file] =>[firstpage_image] =>[orig_patent_app_number] => 16995655 [rel_patent_id] =>[rel_patent_doc_number] =>)
16/995655
Multi-task neural networks with task-specific paths Aug 16, 2020 Issued
Array ( [id] => 16470821 [patent_doc_number] => 20200372358 [patent_country] => US [patent_kind] => A1 [patent_issue_date] => 2020-11-26 [patent_title] => ATTENTION-BASED SEQUENCE TRANSDUCTION NEURAL NETWORKS [patent_app_type] => utility [patent_app_number] => 16/988547 [patent_app_country] => US [patent_app_date] => 2020-08-07 [patent_effective_date] => 0000-00-00 [patent_drawing_sheets_cnt] => 0 [patent_figures_cnt] => 0 [patent_no_of_words] => 8203 [patent_no_of_claims] => 0 [patent_no_of_ind_claims] => -17 [patent_words_short_claim] => 220 [patent_maintenance] => 1 [patent_no_of_assignments] => 0 [patent_current_assignee] =>[type] => publication [pdf_file] =>[firstpage_image] =>[orig_patent_app_number] => 16988547 [rel_patent_id] =>[rel_patent_doc_number] =>)
16/988547
Attention-based sequence transduction neural networks Aug 6, 2020 Issued
Array ( [id] => 16585221 [patent_doc_number] => 20210019623 [patent_country] => US [patent_kind] => A1 [patent_issue_date] => 2021-01-21 [patent_title] => ATTENTION-BASED SEQUENCE TRANSDUCTION NEURAL NETWORKS [patent_app_type] => utility [patent_app_number] => 16/988518 [patent_app_country] => US [patent_app_date] => 2020-08-07 [patent_effective_date] => 0000-00-00 [patent_drawing_sheets_cnt] => 0 [patent_figures_cnt] => 0 [patent_no_of_words] => 8203 [patent_no_of_claims] => 0 [patent_no_of_ind_claims] => -17 [patent_words_short_claim] => 226 [patent_maintenance] => 1 [patent_no_of_assignments] => 0 [patent_current_assignee] =>[type] => publication [pdf_file] =>[firstpage_image] =>[orig_patent_app_number] => 16988518 [rel_patent_id] =>[rel_patent_doc_number] =>)
16/988518
Attention-based sequence transduction neural networks Aug 6, 2020 Issued
Array ( [id] => 17402717 [patent_doc_number] => 20220044808 [patent_country] => US [patent_kind] => A1 [patent_issue_date] => 2022-02-10 [patent_title] => PREDICTIVE MONITORING OF THE GLUCOSE-INSULIN ENDOCRINE METABOLIC REGULATORY SYSTEM [patent_app_type] => utility [patent_app_number] => 16/985759 [patent_app_country] => US [patent_app_date] => 2020-08-05 [patent_effective_date] => 0000-00-00 [patent_drawing_sheets_cnt] => 0 [patent_figures_cnt] => 0 [patent_no_of_words] => 33193 [patent_no_of_claims] => 0 [patent_no_of_ind_claims] => -17 [patent_words_short_claim] => 279 [patent_maintenance] => 1 [patent_no_of_assignments] => 0 [patent_current_assignee] =>[type] => publication [pdf_file] =>[firstpage_image] =>[orig_patent_app_number] => 16985759 [rel_patent_id] =>[rel_patent_doc_number] =>)
16/985759
Predictive monitoring of the glucose-insulin endocrine metabolic regulatory system Aug 4, 2020 Issued
Array ( [id] => 18697506 [patent_doc_number] => 20230327969 [patent_country] => US [patent_kind] => A1 [patent_issue_date] => 2023-10-12 [patent_title] => QUANTUM COMPUTING DEVICE FOR DETERMINING A NETWORK PARAMETER [patent_app_type] => utility [patent_app_number] => 18/018537 [patent_app_country] => US [patent_app_date] => 2020-07-29 [patent_effective_date] => 0000-00-00 [patent_drawing_sheets_cnt] => 0 [patent_figures_cnt] => 0 [patent_no_of_words] => 7436 [patent_no_of_claims] => 0 [patent_no_of_ind_claims] => -15 [patent_words_short_claim] => 2 [patent_maintenance] => 1 [patent_no_of_assignments] => 0 [patent_current_assignee] =>[type] => publication [pdf_file] =>[firstpage_image] =>[orig_patent_app_number] => 18018537 [rel_patent_id] =>[rel_patent_doc_number] =>)
18/018537
QUANTUM COMPUTING DEVICE FOR DETERMINING A NETWORK PARAMETER Jul 28, 2020 Pending
Array ( [id] => 18697506 [patent_doc_number] => 20230327969 [patent_country] => US [patent_kind] => A1 [patent_issue_date] => 2023-10-12 [patent_title] => QUANTUM COMPUTING DEVICE FOR DETERMINING A NETWORK PARAMETER [patent_app_type] => utility [patent_app_number] => 18/018537 [patent_app_country] => US [patent_app_date] => 2020-07-29 [patent_effective_date] => 0000-00-00 [patent_drawing_sheets_cnt] => 0 [patent_figures_cnt] => 0 [patent_no_of_words] => 7436 [patent_no_of_claims] => 0 [patent_no_of_ind_claims] => -15 [patent_words_short_claim] => 2 [patent_maintenance] => 1 [patent_no_of_assignments] => 0 [patent_current_assignee] =>[type] => publication [pdf_file] =>[firstpage_image] =>[orig_patent_app_number] => 18018537 [rel_patent_id] =>[rel_patent_doc_number] =>)
18/018537
QUANTUM COMPUTING DEVICE FOR DETERMINING A NETWORK PARAMETER Jul 28, 2020 Pending
Array ( [id] => 16722744 [patent_doc_number] => 20210089891 [patent_country] => US [patent_kind] => A1 [patent_issue_date] => 2021-03-25 [patent_title] => DEEP REINFORCEMENT LEARNING BASED METHOD FOR SURREPTITIOUSLY GENERATING SIGNALS TO FOOL A RECURRENT NEURAL NETWORK [patent_app_type] => utility [patent_app_number] => 16/937503 [patent_app_country] => US [patent_app_date] => 2020-07-23 [patent_effective_date] => 0000-00-00 [patent_drawing_sheets_cnt] => 0 [patent_figures_cnt] => 0 [patent_no_of_words] => 5785 [patent_no_of_claims] => 0 [patent_no_of_ind_claims] => -15 [patent_words_short_claim] => 135 [patent_maintenance] => 1 [patent_no_of_assignments] => 0 [patent_current_assignee] =>[type] => publication [pdf_file] =>[firstpage_image] =>[orig_patent_app_number] => 16937503 [rel_patent_id] =>[rel_patent_doc_number] =>)
16/937503
Deep reinforcement learning based method for surreptitiously generating signals to fool a recurrent neural network Jul 22, 2020 Issued
Array ( [id] => 16470820 [patent_doc_number] => 20200372357 [patent_country] => US [patent_kind] => A1 [patent_issue_date] => 2020-11-26 [patent_title] => ATTENTION-BASED SEQUENCE TRANSDUCTION NEURAL NETWORKS [patent_app_type] => utility [patent_app_number] => 16/932422 [patent_app_country] => US [patent_app_date] => 2020-07-17 [patent_effective_date] => 0000-00-00 [patent_drawing_sheets_cnt] => 0 [patent_figures_cnt] => 0 [patent_no_of_words] => 8179 [patent_no_of_claims] => 0 [patent_no_of_ind_claims] => -17 [patent_words_short_claim] => 2 [patent_maintenance] => 1 [patent_no_of_assignments] => 0 [patent_current_assignee] =>[type] => publication [pdf_file] =>[firstpage_image] =>[orig_patent_app_number] => 16932422 [rel_patent_id] =>[rel_patent_doc_number] =>)
16/932422
Attention-based sequence transduction neural networks Jul 16, 2020 Issued
Array ( [id] => 18839493 [patent_doc_number] => 11847567 [patent_country] => US [patent_kind] => B1 [patent_issue_date] => 2023-12-19 [patent_title] => Loss-aware replication of neural network layers [patent_app_type] => utility [patent_app_number] => 16/923003 [patent_app_country] => US [patent_app_date] => 2020-07-07 [patent_effective_date] => 0000-00-00 [patent_drawing_sheets_cnt] => 33 [patent_figures_cnt] => 37 [patent_no_of_words] => 44049 [patent_no_of_claims] => 21 [patent_no_of_ind_claims] => 2 [patent_words_short_claim] => 247 [patent_maintenance] => 1 [patent_no_of_assignments] => 0 [patent_current_assignee] =>[type] => patent [pdf_file] =>[firstpage_image] =>[orig_patent_app_number] => 16923003 [rel_patent_id] =>[rel_patent_doc_number] =>)
16/923003
Loss-aware replication of neural network layers Jul 6, 2020 Issued
Array ( [id] => 16379258 [patent_doc_number] => 20200328101 [patent_country] => US [patent_kind] => A1 [patent_issue_date] => 2020-10-15 [patent_title] => SEARCH APPARATUS AND SEARCH METHOD [patent_app_type] => utility [patent_app_number] => 16/911669 [patent_app_country] => US [patent_app_date] => 2020-06-25 [patent_effective_date] => 0000-00-00 [patent_drawing_sheets_cnt] => 0 [patent_figures_cnt] => 0 [patent_no_of_words] => 16109 [patent_no_of_claims] => 0 [patent_no_of_ind_claims] => -16 [patent_words_short_claim] => 290 [patent_maintenance] => 1 [patent_no_of_assignments] => 0 [patent_current_assignee] =>[type] => publication [pdf_file] =>[firstpage_image] =>[orig_patent_app_number] => 16911669 [rel_patent_id] =>[rel_patent_doc_number] =>)
16/911669
SEARCH APPARATUS AND SEARCH METHOD Jun 24, 2020 Abandoned
Array ( [id] => 17779952 [patent_doc_number] => 20220246302 [patent_country] => US [patent_kind] => A1 [patent_issue_date] => 2022-08-04 [patent_title] => DATA ANALYSIS APPARATUS, DATA ANALYSIS METHOD, AND DATA ANALYSIS PROGRAM [patent_app_type] => utility [patent_app_number] => 17/621884 [patent_app_country] => US [patent_app_date] => 2020-06-22 [patent_effective_date] => 0000-00-00 [patent_drawing_sheets_cnt] => 0 [patent_figures_cnt] => 0 [patent_no_of_words] => 5130 [patent_no_of_claims] => 0 [patent_no_of_ind_claims] => -12 [patent_words_short_claim] => 154 [patent_maintenance] => 1 [patent_no_of_assignments] => 0 [patent_current_assignee] =>[type] => publication [pdf_file] =>[firstpage_image] =>[orig_patent_app_number] => 17621884 [rel_patent_id] =>[rel_patent_doc_number] =>)
17/621884
DATA ANALYSIS APPARATUS, DATA ANALYSIS METHOD, AND DATA ANALYSIS PROGRAM Jun 21, 2020 Abandoned
Array ( [id] => 18585013 [patent_doc_number] => 20230267277 [patent_country] => US [patent_kind] => A1 [patent_issue_date] => 2023-08-24 [patent_title] => SYSTEMS AND METHODS FOR USING DOCUMENT ACTIVITY LOGS TO TRAIN MACHINE-LEARNED MODELS FOR DETERMINING DOCUMENT RELEVANCE [patent_app_type] => utility [patent_app_number] => 18/010727 [patent_app_country] => US [patent_app_date] => 2020-06-15 [patent_effective_date] => 0000-00-00 [patent_drawing_sheets_cnt] => 0 [patent_figures_cnt] => 0 [patent_no_of_words] => 18569 [patent_no_of_claims] => 0 [patent_no_of_ind_claims] => -17 [patent_words_short_claim] => 171 [patent_maintenance] => 1 [patent_no_of_assignments] => 0 [patent_current_assignee] =>[type] => publication [pdf_file] =>[firstpage_image] =>[orig_patent_app_number] => 18010727 [rel_patent_id] =>[rel_patent_doc_number] =>)
18/010727
SYSTEMS AND METHODS FOR USING DOCUMENT ACTIVITY LOGS TO TRAIN MACHINE-LEARNED MODELS FOR DETERMINING DOCUMENT RELEVANCE Jun 14, 2020 Pending
Array ( [id] => 18585013 [patent_doc_number] => 20230267277 [patent_country] => US [patent_kind] => A1 [patent_issue_date] => 2023-08-24 [patent_title] => SYSTEMS AND METHODS FOR USING DOCUMENT ACTIVITY LOGS TO TRAIN MACHINE-LEARNED MODELS FOR DETERMINING DOCUMENT RELEVANCE [patent_app_type] => utility [patent_app_number] => 18/010727 [patent_app_country] => US [patent_app_date] => 2020-06-15 [patent_effective_date] => 0000-00-00 [patent_drawing_sheets_cnt] => 0 [patent_figures_cnt] => 0 [patent_no_of_words] => 18569 [patent_no_of_claims] => 0 [patent_no_of_ind_claims] => -17 [patent_words_short_claim] => 171 [patent_maintenance] => 1 [patent_no_of_assignments] => 0 [patent_current_assignee] =>[type] => publication [pdf_file] =>[firstpage_image] =>[orig_patent_app_number] => 18010727 [rel_patent_id] =>[rel_patent_doc_number] =>)
18/010727
SYSTEMS AND METHODS FOR USING DOCUMENT ACTIVITY LOGS TO TRAIN MACHINE-LEARNED MODELS FOR DETERMINING DOCUMENT RELEVANCE Jun 14, 2020 Pending
Array ( [id] => 16285579 [patent_doc_number] => 20200279181 [patent_country] => US [patent_kind] => A1 [patent_issue_date] => 2020-09-03 [patent_title] => Multi-Platform Machine Learning Systems [patent_app_type] => utility [patent_app_number] => 16/878120 [patent_app_country] => US [patent_app_date] => 2020-05-19 [patent_effective_date] => 0000-00-00 [patent_drawing_sheets_cnt] => 0 [patent_figures_cnt] => 0 [patent_no_of_words] => 11367 [patent_no_of_claims] => 0 [patent_no_of_ind_claims] => -17 [patent_words_short_claim] => 153 [patent_maintenance] => 1 [patent_no_of_assignments] => 0 [patent_current_assignee] =>[type] => publication [pdf_file] =>[firstpage_image] =>[orig_patent_app_number] => 16878120 [rel_patent_id] =>[rel_patent_doc_number] =>)
16/878120
Multi-platform machine learning systems May 18, 2020 Issued
Array ( [id] => 17231200 [patent_doc_number] => 20210357757 [patent_country] => US [patent_kind] => A1 [patent_issue_date] => 2021-11-18 [patent_title] => CUSTOMIZING AN ARTIFICIAL INTELLIGENCE MODEL TO PROCESS A DATA SET [patent_app_type] => utility [patent_app_number] => 16/875792 [patent_app_country] => US [patent_app_date] => 2020-05-15 [patent_effective_date] => 0000-00-00 [patent_drawing_sheets_cnt] => 0 [patent_figures_cnt] => 0 [patent_no_of_words] => 7333 [patent_no_of_claims] => 0 [patent_no_of_ind_claims] => -18 [patent_words_short_claim] => 97 [patent_maintenance] => 1 [patent_no_of_assignments] => 0 [patent_current_assignee] =>[type] => publication [pdf_file] =>[firstpage_image] =>[orig_patent_app_number] => 16875792 [rel_patent_id] =>[rel_patent_doc_number] =>)
16/875792
Customizing an artificial intelligence model to process a data set May 14, 2020 Issued
Array ( [id] => 16378549 [patent_doc_number] => 20200327391 [patent_country] => US [patent_kind] => A1 [patent_issue_date] => 2020-10-15 [patent_title] => SYSTEM AND METHOD FOR PARALLELIZING CONVOLUTIONAL NEURAL NETWORKS [patent_app_type] => utility [patent_app_number] => 16/859815 [patent_app_country] => US [patent_app_date] => 2020-04-27 [patent_effective_date] => 0000-00-00 [patent_drawing_sheets_cnt] => 0 [patent_figures_cnt] => 0 [patent_no_of_words] => 2783 [patent_no_of_claims] => 0 [patent_no_of_ind_claims] => -17 [patent_words_short_claim] => 156 [patent_maintenance] => 1 [patent_no_of_assignments] => 0 [patent_current_assignee] =>[type] => publication [pdf_file] =>[firstpage_image] =>[orig_patent_app_number] => 16859815 [rel_patent_id] =>[rel_patent_doc_number] =>)
16/859815
System and method for parallelizing convolutional neural networks Apr 26, 2020 Issued
Array ( [id] => 16363641 [patent_doc_number] => 20200320392 [patent_country] => US [patent_kind] => A1 [patent_issue_date] => 2020-10-08 [patent_title] => OPTIMIZATION PROCESSING FOR NEURAL NETWORK MODEL [patent_app_type] => utility [patent_app_number] => 16/850792 [patent_app_country] => US [patent_app_date] => 2020-04-16 [patent_effective_date] => 0000-00-00 [patent_drawing_sheets_cnt] => 0 [patent_figures_cnt] => 0 [patent_no_of_words] => 5806 [patent_no_of_claims] => 0 [patent_no_of_ind_claims] => -17 [patent_words_short_claim] => 132 [patent_maintenance] => 1 [patent_no_of_assignments] => 0 [patent_current_assignee] =>[type] => publication [pdf_file] =>[firstpage_image] =>[orig_patent_app_number] => 16850792 [rel_patent_id] =>[rel_patent_doc_number] =>)
16/850792
Optimization processing for neural network model Apr 15, 2020 Issued
Array ( [id] => 16378598 [patent_doc_number] => 20200327440 [patent_country] => US [patent_kind] => A1 [patent_issue_date] => 2020-10-15 [patent_title] => Discrete Optimization Using Continuous Latent Space [patent_app_type] => utility [patent_app_number] => 16/844011 [patent_app_country] => US [patent_app_date] => 2020-04-09 [patent_effective_date] => 0000-00-00 [patent_drawing_sheets_cnt] => 0 [patent_figures_cnt] => 0 [patent_no_of_words] => 8726 [patent_no_of_claims] => 0 [patent_no_of_ind_claims] => -10 [patent_words_short_claim] => 280 [patent_maintenance] => 1 [patent_no_of_assignments] => 0 [patent_current_assignee] =>[type] => publication [pdf_file] =>[firstpage_image] =>[orig_patent_app_number] => 16844011 [rel_patent_id] =>[rel_patent_doc_number] =>)
16/844011
Discrete Optimization Using Continuous Latent Space Apr 8, 2020 Abandoned
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