Ladder Networks for Semi-Supervised Hyperspectral Image Classification. - Julian Büchel; Okan K. Ersoy (CoRR, 2018)

Implementing Efficient Balanced Networks with Mixed-Signal Spike-Based Learning Circuits. - Julian Büchel; Jonathan Kakon; Michel Perez; Giacomo Indiveri (ISCAS, 2021)

Supervised training of spiking neural networks for robust deployment on mixed-signal neuromorphic processors. - Julian Büchel; Dmitrii Zendrikov; Sergio M. G. Solinas; Giacomo Indiveri; Dylan R. Muir (CoRR, 2021)

Network insensitivity to parameter noise via adversarial regularization. - Julian Büchel; Fynn Faber; Dylan R. Muir (CoRR, 2021)

Adversarial Attacks on Spiking Convolutional Networks for Event-based Vision. - Julian Büchel; Gregor Lenz; Yalun Hu; Sadique Sheik; Martino Sorbaro 001 (CoRR, 2021)

AnalogNets: ML-HW Co-Design of Noise-robust TinyML Models and Always-On Analog Compute-in-Memory Accelerator. - Chuteng Zhou; Fernando García-Redondo; Julian Büchel; Irem Boybat; Xavier Timoneda Comas; S. R. Nandakumar; Shidhartha Das; Abu Sebastian; Manuel Le Gallo; Paul N. Whatmough (CoRR, 2021)

Network Insensitivity to Parameter Noise via Parameter Attack During Training. - Julian Büchel; Fynn Firouz Faber; Dylan Richard Muir (ICLR, 2022)

A 64-core mixed-signal in-memory compute chip based on phase-change memory for deep neural network inference. - Manuel Le Gallo; Riduan Khaddam-Aljameh; Milos Stanisavljevic; Athanasios Vasilopoulos; Benedikt Kersting; Martino Dazzi; Geethan Karunaratne; Matthias Braendli; Abhairaj Singh; Silvia M. Mueller; Julian Büchel; Xavier Timoneda Comas; et al. (CoRR, 2022)

ML-HW Co-Design of Noise-Robust TinyML Models and Always-On Analog Compute-in-Memory Edge Accelerator. - Chuteng Zhou; Fernando García-Redondo; Julian Büchel; Irem Boybat; Xavier Timoneda Comas; S. R. Nandakumar; Shidhartha Das; Abu Sebastian; Manuel Le Gallo; Paul N. Whatmough (IEEE Micro, 2022)

Gradient descent-based programming of analog in-memory computing cores. - Julian Büchel; Athanasios Vasilopoulos; Benedikt Kersting; Frédéric Odermatt; Kevin Brew; Injo Ok; Samuel Choi; Iqbal Saraf; Victor Chan; Timothy Philip; Nicole Saulnier; Vijay Narayanan; et al. (CoRR, 2023)

Using the IBM Analog In-Memory Hardware Acceleration Kit for Neural Network Training and Inference. - Manuel Le Gallo; Corey Lammie; Julian Büchel; Fabio Carta; Omobayode Fagbohungbe; Charles Mackin; Hsinyu Tsai; Vijay Narayanan; Abu Sebastian; Kaoutar El Maghraoui; Malte J. Rasch (CoRR, 2023)

Programming Weights to Analog In-Memory Computing Cores by Direct Minimization of the Matrix-Vector Multiplication Error. - Julian Büchel; Athanasios Vasilopoulos; Benedikt Kersting; Corey Lammie; Kevin Brew; Timothy Philip; Nicole Saulnier; Vijay Narayanan; Manuel Le Gallo; Abu Sebastian (IEEE J. Emerg. Sel. Topics Circuits Syst., 2023)

Analog AI as a Service: A Cloud Platform for In-Memory Computing. - Kaoutar El Maghraoui; Kim Tran; Kurtis Ruby; Borja Godoy; Jordan Murray; Manuel Le Gallo-Bourdeau; Todd Deshane; Pablo Gonzalez; Diego Moreda; Hadjer Benmeziane; Corey Liam Lammie; Julian Büchel; et al. (SSE, 2024)

Improving the Accuracy of Analog-Based In-Memory Computing Accelerators Post-Training. - Corey Lammie; Athanasios Vasilopoulos; Julian Büchel; Giacomo Camposampiero; Manuel Le Gallo; Malte J. Rasch; Abu Sebastian (ISCAS, 2024)

In-Materia Speech Recognition. - Mohamadreza Zolfagharinejad; Julian Büchel; Lorenzo Cassola; Sachin Kinge; Syed Ghazi Sarwat; Abu Sebastian; Wilfred G. van der Wiel (CoRR, 2024)

Kernel Approximation using Analog In-Memory Computing. - Julian Büchel; Giacomo Camposampiero; Athanasios Vasilopoulos; Corey Lammie; Manuel Le Gallo; Abbas Rahimi; Abu Sebastian (CoRR, 2024)

The Inherent Adversarial Robustness of Analog In-Memory Computing. - Corey Lammie; Julian Büchel; Athanasios Vasilopoulos; Manuel Le Gallo; Abu Sebastian (CoRR, 2024)

Kernel approximation using analogue in-memory computing. - Julian Büchel; Giacomo Camposampiero; Athanasios Vasilopoulos; Corey Lammie; Manuel Le Gallo; Abbas Rahimi; Abu Sebastian (Nat. Mac. Intell., 2024)

Analog-AI Hardware Accelerators for Low-Latency Transformer-Based Language Models (Invited). - Geoffrey W. Burr; H. Tsai; Irem Boybat; William Andrew Simon; Julian Büchel; Athanasios Vasilopoulos; Pritish Narayanan; Andrea Fasoli; Kohji Hosokawa; Manuel Le Gallo; M. Ishii; Yasuteru Kohda; et al. (CICC, 2025)

Analog AI Accelerators for Transformer-based Language Models: Hardware, Workload, and Power Performance. - H. Tsai; Hadjer Benmeziane; Irem Boybat; Julian Büchel; Pritish Narayanan; Manuel Le Gallo; S. Jain; Athanasios Vasilopoulos; W. Simon; Kohji Hosokawa; M. Ishii; Yasuteru Kohda; et al. (IMW, 2025)

Live Demonstration: Automated DNN Deployment on the IBM HERMES Project Chip. - Corey Lammie; Julian Büchel; Athanasios Vasilopoulos; Giacomo Camposampiero; Lionel Noussi; William Andrew Simon; Manuel Le Gallo; Abu Sebastian (ISCAS, 2025)

A framework for analog-digital mixed-precision neural network training and inference. - Athanasios Vasilopoulos; Emma Boulharts; Corey Lammie; Julian Büchel; Hadjer Benmeziane; Manuel Le Gallo; Abu Sebastian (ISCAS, 2025)

Author Correction: Kernel approximation using analogue in-memory computing. - Julian Büchel; Giacomo Camposampiero; Athanasios Vasilopoulos; Corey Lammie; Manuel Le Gallo; Abbas Rahimi; Abu Sebastian (Nat. Mac. Intell., 2025)

Efficient scaling of large language models with mixture of experts and 3D analog in-memory computing. - Julian Büchel; Athanasios Vasilopoulos; William Andrew Simon; Irem Boybat; Hsinyu Tsai; Geoffrey W. Burr; Hernan Castro; Bill Filipiak; Manuel Le Gallo; Abbas Rahimi; Vijay Narayanan; Abu Sebastian (Nat. Comput. Sci., 2025)

Analog Foundation Models. - Julian Büchel; Iason Chalas; Giovanni Acampa; An Chen 002; Omobayode Fagbohungbe; Sidney Tsai; Kaoutar El Maghraoui; Manuel Le Gallo; Abbas Rahimi; Abu Sebastian (CoRR, 2025)

Rapid yet accurate Tile-circuit and device modeling for Analog In-Memory Computing. - Jose Luquin; Charles Mackin; Stefano Ambrogio; An Chen 002; F. Baldi; G. Miralles; Malte J. Rasch; Julian Büchel; M. Lalwani; W. Ponghiran; Paul Solomon; Hsinyu Tsai; et al. (CoRR, 2025)