|Fully hardware-implemented memristor convolutional neural network|
P Yao, H Wu, B Gao, J Tang, Q Zhang, W Zhang, JJ Yang, H Qian
Nature 577 (7792), 641-646, 2020
|Fully memristive neural networks for pattern classification with unsupervised learning|
Z Wang, S Joshi, S Savel’ev, W Song, R Midya, Y Li, M Rao, P Yan, ...
Nature Electronics 1 (2), 137-145, 2018
|Face classification using electronic synapses|
P Yao, H Wu, B Gao, SB Eryilmaz, X Huang, W Zhang, Q Zhang, N Deng, ...
Nature communications 8 (1), 1-8, 2017
|Resistive switching materials for information processing|
Z Wang, H Wu, GW Burr, CS Hwang, KL Wang, Q Xia, JJ Yang
Nature Reviews Materials 5 (3), 173-195, 2020
|Towards artificial general intelligence with hybrid Tianjic chip architecture|
J Pei, L Deng, S Song, M Zhao, Y Zhang, S Wu, G Wang, Z Zou, Z Wu, ...
Nature 572 (7767), 106-111, 2019
|Recommended methods to study resistive switching devices|
M Lanza, HSP Wong, E Pop, D Ielmini, D Strukov, BC Regan, L Larcher, ...
Advanced Electronic Materials 5 (1), 1800143, 2019
|Bridging biological and artificial neural networks with emerging neuromorphic devices: fundamentals, progress, and challenges|
J Tang, F Yuan, X Shen, Z Wang, M Rao, Y He, Y Sun, X Li, W Zhang, Y Li, ...
Advanced Materials 31 (49), 1902761, 2019
|An artificial nociceptor based on a diffusive memristor|
JH Yoon, Z Wang, KM Kim, H Wu, V Ravichandran, Q Xia, CS Hwang, ...
Nature communications 9 (1), 1-9, 2018
|Understanding memristive switching via in situ characterization and device modeling|
W Sun, B Gao, M Chi, Q Xia, JJ Yang, H Qian, H Wu
Nature communications 10 (1), 1-13, 2019
|Neuro-inspired computing chips|
W Zhang, B Gao, J Tang, P Yao, S Yu, MF Chang, HJ Yoo, H Qian, H Wu
Nature electronics 3 (7), 371-382, 2020
|Threshold switching of Ag or Cu in dielectrics: materials, mechanism, and applications|
Z Wang, M Rao, R Midya, S Joshi, H Jiang, P Lin, W Song, S Asapu, ...
Advanced Functional Materials 28 (6), 1704862, 2018
|Binary neural network with 16 Mb RRAM macro chip for classification and online training|
S Yu, Z Li, PY Chen, H Wu, B Gao, D Wang, W Wu, H Qian
2016 IEEE International Electron Devices Meeting (IEDM), 16.2. 1-16.2. 4, 2016
|Scaling-up resistive synaptic arrays for neuro-inspired architecture: Challenges and prospect|
S Yu, PY Chen, Y Cao, L Xia, Y Wang, H Wu
2015 IEEE International Electron Devices Meeting (IEDM), 17.3. 1-17.3. 4, 2015
|Synthesis and characterization of vertically standing MoS2 nanosheets|
H Li, H Wu, S Yuan, H Qian
Scientific reports 6 (1), 1-9, 2016
|Graphene oxide quantum dots based memristors with progressive conduction tuning for artificial synaptic learning|
X Yan, L Zhang, H Chen, X Li, J Wang, Q Liu, C Lu, J Chen, H Wu, P Zhou
Advanced Functional Materials 28 (40), 1803728, 2018
|Capacitive neural network with neuro-transistors|
Z Wang, M Rao, JW Han, J Zhang, P Lin, Y Li, C Li, W Song, S Asapu, ...
Nature communications 9 (1), 1-10, 2018
|Improving Analog Switching in HfOx-Based Resistive Memory With a Thermal Enhanced Layer|
W Wu, H Wu, B Gao, N Deng, S Yu, H Qian
IEEE Electron Device Letters 38 (8), 1019-1022, 2017
|Large-scale neuromorphic optoelectronic computing with a reconfigurable diffractive processing unit|
T Zhou, X Lin, J Wu, Y Chen, H Xie, Y Li, J Fan, H Wu, L Fang, Q Dai
Nature Photonics 15 (5), 367-373, 2021
|In situ training of feed-forward and recurrent convolutional memristor networks|
Z Wang, C Li, P Lin, M Rao, Y Nie, W Song, Q Qiu, Y Li, P Yan, ...
Nature Machine Intelligence 1 (9), 434-442, 2019
|Memory materials and devices: From concept to application|
Z Zhang, Z Wang, T Shi, C Bi, F Rao, Y Cai, Q Liu, H Wu, P Zhou
InfoMat 2 (2), 261-290, 2020