Tayfun Gokmen - RankMe

33 papers A* 1A 2C 1Journal 24Unranked 5

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Dynamic Symmetric Point Tracking: Tackling Non-ideal Reference in Analog In-memory Training. CoRR Quan Xiao, Jindan Li, Zhaoxian Wu, Tayfun Gokmen, Tianyi Chen
2025	J	`jnl`	Analog In-memory Training on General Non-ideal Resistive Elements: The Impact of Response Functions. CoRR Zhaoxian Wu, Quan Xiao, Tayfun Gokmen, Omobayode Fagbohungbe, Tianyi Chen
2025	C	`conf`	Assessing the Performance of Analog Training for Transfer Learning. ISCAS Omobayode Fagbohungbe, Corey Lammie, Malte J. Rasch, Takashi Ando, Tayfun Gokmen, Vijay Narayanan
2025	J	`jnl`	Assessing the Performance of Analog Training for Transfer Learning. CoRR Omobayode Fagbohungbe, Corey Lammie, Malte J. Rasch, Takashi Ando, Tayfun Gokmen, Vijay Narayanan
2025	J	`jnl`	Assessing the Performance of Analog Training for Transfer Learning. IEEE Trans. Circuits Syst. II Express Briefs Omobayode Fagbohungbe, Corey Lammie, Malte J. Rasch, Takashi Ando, Tayfun Gokmen, Vijay Narayanan
2025	J	`jnl`	In-memory Training on Analog Devices with Limited Conductance States via Multi-tile Residual Learning. CoRR Jindan Li, Zhaoxian Wu, Gaowen Liu, Tayfun Gokmen, Tianyi Chen
2025	A	`conf`	NORA: Noise-Optimized Rescaling of LLMs on Analog Compute-in-Memory Accelerators. DATE Yayue Hou, Hsinyu Tsai, Kaoutar El Maghraoui, Tayfun Gokmen, Geoffrey W. Burr, Liu Liu
2024	J	`jnl`	Multi-Function Multi-Way Analog Technology for Sustainable Machine Intelligence Computation. CoRR Vassilis Kalantzis, Mark S. Squillante, Shashanka Ubaru, Tayfun Gokmen, Chai Wah Wu, Anshul Gupta, Haim Avron, Tomasz Nowicki, Malte J. Rasch, O. Murat Onen, Vanessa López-Marrero, Effendi Leobandung, Yasuteru Kohda, Wilfried Haensch, Lior Horesh
2024	J	`jnl`	Pipeline Gradient-based Model Training on Analog In-memory Accelerators. CoRR Zhaoxian Wu, Quan Xiao, Tayfun Gokmen, Hsinyu Tsai, Kaoutar El Maghraoui, Tianyi Chen
2024	A*	`conf`	Towards Exact Gradient-based Training on Analog In-memory Computing. NeurIPS Zhaoxian Wu, Tayfun Gokmen, Malte J. Rasch, Tianyi Chen
2024	J	`jnl`	Towards Exact Gradient-based Training on Analog In-memory Computing. CoRR Zhaoxian Wu, Tayfun Gokmen, Malte J. Rasch, Tianyi Chen
2023	J	`jnl`	Fast offset corrected in-memory training. CoRR Malte J. Rasch, Fabio Carta, Omobayode Fagbohungbe, Tayfun Gokmen
2023	—	`conf`	Solving Sparse Linear Systems via Flexible GMRES with In-Memory Analog Preconditioning. HPEC Vasileios Kalantzis, Mark S. Squillante, Chai Wah Wu, Anshul Gupta, Shashanka Ubaru, Tayfun Gokmen, Lior Horesh
2022	J	`jnl`	Neural Network Training With Asymmetric Crosspoint Elements. Frontiers Artif. Intell. O. Murat Onen, Tayfun Gokmen, Teodor K. Todorov, Tomasz Nowicki, Jesús A. del Alamo, John Rozen, Wilfried Haensch, Seyoung Kim
2022	J	`jnl`	Neural Network Training with Asymmetric Crosspoint Elements. CoRR O. Murat Onen, Tayfun Gokmen, Teodor K. Todorov, Tomasz Nowicki, Jesús A. del Alamo, John Rozen, Wilfried Haensch, Seyoung Kim
2021	—	`conf`	A Flexible and Fast PyTorch Toolkit for Simulating Training and Inference on Analog Crossbar Arrays. AICAS Malte J. Rasch, Diego Moreda, Tayfun Gokmen, Manuel Le Gallo, Fabio Carta, Cindy Goldberg, Kaoutar El Maghraoui, Abu Sebastian, Vijay Narayanan
2021	J	`jnl`	A flexible and fast PyTorch toolkit for simulating training and inference on analog crossbar arrays. CoRR Malte J. Rasch, Diego Moreda, Tayfun Gokmen, Manuel Le Gallo, Fabio Carta, Cindy Goldberg, Kaoutar El Maghraoui, Abu Sebastian, Vijay Narayanan
2021	J	`jnl`	Enabling Training of Neural Networks on Noisy Hardware. Frontiers Artif. Intell. Tayfun Gokmen
2021	—	`conf`	Solving sparse linear systems with approximate inverse preconditioners on analog devices. HPEC Vasileios Kalantzis, Anshul Gupta, Lior Horesh, Tomasz Nowicki, Mark S. Squillante, Chai Wah Wu, Tayfun Gokmen, Haim Avron
2020	A	`conf`	Emerging Neural Workloads and Their Impact on Hardware. DATE David Brooks, Martin M. Frank, Tayfun Gokmen, Udit Gupta, Xiaobo Sharon Hu, Shubham Jain, Ann Franchesca Laguna, Michael T. Niemier, Ian O'Connor, Anand Raghunathan, Ashish Ranjan, Dayane Reis, Jacob R. Stevens, Carole-Jean Wu, Xunzhao Yin
2020	J	`jnl`	Training Large-scale Artificial Neural Networks on Simulated Resistive Crossbar Arrays. IEEE Des. Test Malte J. Rasch, Tayfun Gokmen, Wilfried Haensch
2019	J	`jnl`	Algorithm for Training Neural Networks on Resistive Device Arrays. CoRR Tayfun Gokmen, Wilfried Haensch
2019	J	`jnl`	Design and Characterization of Superconducting Nanowire-Based Processors for Acceleration of Deep Neural Network Training. CoRR O. Murat Onen, Brenden A. Butters, Emily Toomey, Tayfun Gokmen, Karl K. Berggren
2019	J	`jnl`	Neural network accelerator design with resistive crossbars: Opportunities and challenges. IBM J. Res. Dev. Shubham Jain, Aayush Ankit, Indranil Chakraborty, Tayfun Gokmen, Malte J. Rasch, Wilfried Haensch, Kaushik Roy, Anand Raghunathan
2019	—	`conf`	Reliability Challenges with Materials for Analog Computing. IRPS Eduard A. Cartier, Wanki Kim, Nanbo Gong, Tayfun Gokmen, Martin M. Frank, Douglas M. Bishop, Youngseok Kim, Seyoung Kim, Takashi Ando, Ernest Y. Wu, Praneet Adusumilli, John Rozen, Paul M. Solomon, Wilfried Haensch, Matthew J. BrightSky, Abu Sebastian, Geoffrey W. Burr, Vijay Narayanan
2019	J	`jnl`	The Next Generation of Deep Learning Hardware: Analog Computing. Proc. IEEE Wilfried Haensch, Tayfun Gokmen, Ruchir Puri
2019	J	`jnl`	Training large-scale ANNs on simulated resistive crossbar arrays. CoRR Malte J. Rasch, Tayfun Gokmen, Wilfried Haensch
2019	J	`jnl`	Zero-shifting Technique for Deep Neural Network Training on Resistive Cross-point Arrays. CoRR Hyungjun Kim, Malte J. Rasch, Tayfun Gokmen, Takashi Ando, Hiroyuki Miyazoe, Jae-Joon Kim, John Rozen, Seyoung Kim
2018	J	`jnl`	Efficient ConvNets for Analog Arrays. CoRR Malte J. Rasch, Tayfun Gokmen, Mattia Rigotti, Wilfried Haensch
2018	J	`jnl`	Training LSTM Networks with Resistive Cross-Point Devices. CoRR Tayfun Gokmen, Malte J. Rasch, Wilfried Haensch
2017	J	`jnl`	Analog CMOS-based Resistive Processing Unit for Deep Neural Network Training. CoRR Seyoung Kim, Tayfun Gokmen, Hyung-Min Lee, Wilfried E. Haensch
2017	—	`conf`	Analog CMOS-based resistive processing unit for deep neural network training. MWSCAS Seyoung Kim, Tayfun Gokmen, Hyung-Min Lee, Wilfried E. Haensch
2017	J	`jnl`	Training Deep Convolutional Neural Networks with Resistive Cross-Point Devices. CoRR Tayfun Gokmen, O. Murat Onen, Wilfried Haensch