CrowdStrike, Inc. et al. - IPR2025-01399

Explore the PTAB proceeding IPR2025-01399 filed by CrowdStrike, Inc. et al. on Sep 26, 2025. This includes filing dates, application numbers, tech centers, patent numbers, and current case status.

Case Details

Proceeding Number
IPR2025-01399
Filing Date
Sep 26, 2025
Petitioner
CrowdStrike, Inc. et al.
Status
Petition filed
Respondent Application Number
18154727
Respondent Tech Center
2600
Respondent Patent Number
11775831

Proceeding Decision New

Decision pending - set alert to receive updates

Proceeding Documents

The table below shows documents filed in the case, listing each document name, filing date, document type, and filing party. Tracking these filings indicates the activity of the parties involved in the case, and the types of documents filed can provide insights into the legal strategies being employed.

Document NameFiling DateCategoryFiling Party

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EX1001-U.S. Patent No. 11,775,831

Sep 26, 2025EXHIBITPETITIONER

EX1004-Takayuki Ujiie et al., Approximated Prediction Strategy for Reducing

Sep 26, 2025EXHIBITPETITIONER

EX1005-Moons, et al Energy-Efficient ConvNets Through Approximate Computing

Sep 26, 2025EXHIBITPETITIONER

EX1006-Himanshu Kaul et al., A 21.5M-Query-Vectors/s 3.37nJ/Vector Reconfig

Sep 26, 2025EXHIBITPETITIONER

EX1007- U.S. Patent Application Publication No. 20160259995A1 to Ishii

Sep 26, 2025EXHIBITPETITIONER

EX1008-U.S. Patent Application Publication No. 2016/0259994 A1 to Ravindran

Sep 26, 2025EXHIBITPETITIONER

EX1009-Declaration of June Munford

Sep 26, 2025EXHIBITPETITIONER

EX1010-Declaration of Gordon MacPherson

Sep 26, 2025EXHIBITPETITIONER

EX1011-Matthieu Courbariaux et al., Binarized Neural Networks: Training Neu

Sep 26, 2025EXHIBITPETITIONER

EX1012-Minkyu Kim et al., An Energy-Efficient Deep Convolutional Neural Net

Sep 26, 2025EXHIBITPETITIONER

EX1013-Yann LeCun et al., Gradient-Based Learning Applied to Document Recog

Sep 26, 2025EXHIBITPETITIONER

EX1014-Jiuxiang Gu et al., Recent Advances in Convolutional Neural Networks

Sep 26, 2025EXHIBITPETITIONER

EX1015-Dominik Scherer et al., Evaluation of Pooling Operations in Convolut

Sep 26, 2025EXHIBITPETITIONER

EX1016-U.S. Patent No. 9,886,948 to Garimella et al.

Sep 26, 2025EXHIBITPETITIONER

EX1017-Dingjun Yu et al., Mixed Pooling for Convolutional Neural Networks

Sep 26, 2025EXHIBITPETITIONER

EX1018-Alex Krizhevsky et al., ImageNet Classification with Deep Convolutio

Sep 26, 2025EXHIBITPETITIONER

EX1019-Thomas L. Floyd, Digital Fundamentals, 11th ed., Pearson Education L

Sep 26, 2025EXHIBITPETITIONER

EX1021-Yoshua Bengio et al., Estimating or Propagating Gradients Through St

Sep 26, 2025EXHIBITPETITIONER

EX1022-Emmanuel Bengio et al., Conditional Computation in Neural Networks

Sep 26, 2025EXHIBITPETITIONER

EX1023-Vincent Vanhoucke et al., Improving the speed of neural networks on

Sep 26, 2025EXHIBITPETITIONER

EX1024-Patrick Judd et al., Reduced-Precision Strategies for Bounded Memory

Sep 26, 2025EXHIBITPETITIONER

EX1025-Microsoft Computer Dictionary, 3rd ed., 1997, excerpts

Sep 26, 2025EXHIBITPETITIONER

EX1026-Song Han et al., EIE: Efficient Inference Engine on Compressed Deep

Sep 26, 2025EXHIBITPETITIONER

EX1027-Vinay K. Chippa et al., Analysis and Characterization of Inherent Ap

Sep 26, 2025EXHIBITPETITIONER

EX1028-Pakorn Watanachaturaporn et al., Hyperspectral Image Classification

Sep 26, 2025EXHIBITPETITIONER

EX1029-Wei Wen et al., An EDA Framework for Large Scale Hybrid Neuromorphic

Sep 26, 2025EXHIBITPETITIONER

EX1031-Yann LeCun et al., Deep learning, Nature Vol. 521 (May 28, 2015)

Sep 26, 2025EXHIBITPETITIONER

EX1002-File History for US Patent 11755831

Sep 26, 2025EXHIBITPETITIONER

EX1032-Ahmed AK Tahir, Integrating artificial neural network and classical

Sep 26, 2025EXHIBITPETITIONER

EX1003-Declaration of Eli Saber, Ph.D

Sep 26, 2025EXHIBITPETITIONER

Petition for Inter Partes Review of U.S. Patent No. 11,755,831

Sep 26, 2025PAPERPETITIONER

Petitioner Power of Attorney

Sep 26, 2025PAPERPETITIONER