A Complete Real-Time Feature Extraction and Matching System Based on Semantic Kernels Binarized. - Michael Schaffner; Pascal A. Hager; Lukas Cavigelli; Z. Fang; Pierre Greisen; Frank K. Gürkaynak; Aljoscha Smolic; Hubert Kaeslin; Luca Benini (VLSI-SoC (Selected Papers), 2013)

A real-time 720p feature extraction core based on Semantic Kernels Binarized. - Michael Schaffner; Pascal Hager; Lukas Cavigelli; Pierre Greisen; Frank K. Gürkaynak; Hubert Kaeslin (VLSI-SoC, 2013)

Accelerating real-time embedded scene labeling with convolutional networks. - Lukas Cavigelli; Michele Magno; Luca Benini (DAC, 2015)

Origami: A Convolutional Network Accelerator. - Lukas Cavigelli; David Gschwend; Christoph Mayer 007; Samuel Willi; Beat Muheim; Luca Benini (ACM Great Lakes Symposium on VLSI, 2015)

Ultra-Low Power Context Recognition Fusing Sensor Data from an Energy-Neutral Smart Watch. - Michele Magno; Lukas Cavigelli; Renzo Andri; Luca Benini (IoT 360 (2), 2015)

YodaNN: An Ultra-Low Power Convolutional Neural Network Accelerator Based on Binary Weights. - Renzo Andri; Lukas Cavigelli; Davide Rossi; Luca Benini (ISVLSI, 2016)

Computationally Efficient Target Classification in Multispectral Image Data with Deep Neural Networks. - Lukas Cavigelli; Dominic Bernath; Michele Magno; Luca Benini (CoRR, 2016)

InfiniTime: Multi-sensor wearable bracelet with human body harvesting. - Michele Magno; Davide Brunelli; Lukas Sigrist; Renzo Andri; Lukas Cavigelli; Andres Gomez 001; Luca Benini (Sustain. Comput. Informatics Syst., 2016)

Impact of temporal subsampling on accuracy and performance in practical video classification. - Florian Scheidegger; Lukas Cavigelli; Michael Schaffner; A. Cristiano I. Malossi; Constantine Bekas; Luca Benini (EUSIPCO, 2017)

Deep structured features for semantic segmentation. - Michael Tschannen; Lukas Cavigelli; Fabian Mentzer; Thomas Wiatowski; Luca Benini (EUSIPCO, 2017)

CBinfer: Change-Based Inference for Convolutional Neural Networks on Video Data. - Lukas Cavigelli; Philippe Degen; Luca Benini (ICDSC, 2017)

CAS-CNN: A deep convolutional neural network for image compression artifact suppression. - Lukas Cavigelli; Pascal Hager; Luca Benini (IJCNN, 2017)

Soft-to-Hard Vector Quantization for End-to-End Learning Compressible Representations. - Eirikur Agustsson; Fabian Mentzer; Michael Tschannen; Lukas Cavigelli; Radu Timofte; Luca Benini; Luc Van Gool (NIPS, 2017)

Soft-to-Hard Vector Quantization for End-to-End Learned Compression of Images and Neural Networks. - Eirikur Agustsson; Fabian Mentzer; Michael Tschannen; Lukas Cavigelli; Radu Timofte; Luca Benini; Luc Van Gool (CoRR, 2017)

Efficient Convolutional Neural Network For Audio Event Detection. - Matthias Meyer 005; Lukas Cavigelli; Lothar Thiele (CoRR, 2017)

Chipmunk: A Systolically Scalable 0.9 mm2, 3.08 Gop/s/mW @ 1.2 mW Accelerator for Near-Sensor Recurrent Neural Network Inference. - Francesco Conti 001; Lukas Cavigelli; Gianna Paulin; Igor Susmelj; Luca Benini (CoRR, 2017)

Origami: A 803-GOp/s/W Convolutional Network Accelerator. - Lukas Cavigelli; Luca Benini (IEEE Trans. Circuits Syst. Video Technol., 2017)

Embedded Classification of Local Field Potentials Recorded from Rat Barrel Cortex with Implanted Multi-Electrode Array. - Xiaying Wang; Michele Magno; Lukas Cavigelli; Mufti Mahmud; Claudia Cecchetto; Stefano Vassanelli; Luca Benini (BioCAS, 2018)

Chipmunk: A systolically scalable 0.9 mm2, 3.08Gop/s/mW @ 1.2 mW accelerator for near-sensor recurrent neural network inference. - Francesco Conti 001; Lukas Cavigelli; Gianna Paulin; Igor Susmelj; Luca Benini (CICC, 2018)

XNORBIN: A 95 TOp/s/W hardware accelerator for binary convolutional neural networks. - Andrawes Al Bahou; Geethan Karunaratne; Renzo Andri; Lukas Cavigelli; Luca Benini (COOL CHIPS, 2018)

Fast and Accurate Multiclass Inference for MI-BCIs Using Large Multiscale Temporal and Spectral Features. - Michael Hersche; Tino Rellstab; Pasquale Davide Schiavone; Lukas Cavigelli; Luca Benini; Abbas Rahimi (EUSIPCO, 2018)

Rat Cortical Layers Classification extracting Evoked Local Field Potential Images with Implanted Multi-Electrode Sensor. - Xiaying Wang; Michele Magno; Lukas Cavigelli; Mufti Mahmud; Claudia Cecchetto; Stefano Vassanelli; Luca Benini (HealthCom, 2018)

Hydra: An Accelerator for Real-Time Edge-Aware Permeability Filtering in 65nm CMOS. - Manuel Eggimann; Christelle Gloor; Florian Scheidegger; Lukas Cavigelli; Michael Schaffner; Aljosa Smolic; Luca Benini (ISCAS, 2018)

Design Automation for Binarized Neural Networks: A Quantum Leap Opportunity? - Manuele Rusci; Lukas Cavigelli; Luca Benini (ISCAS, 2018)

Hyperdrive: A Systolically Scalable Binary-Weight CNN Inference Engine for mW IoT End-Nodes. - Renzo Andri; Lukas Cavigelli; Davide Rossi; Luca Benini (ISVLSI, 2018)

YodaNN: An Architecture for Ultralow Power Binary-Weight CNN Acceleration. - Renzo Andri; Lukas Cavigelli; Davide Rossi; Luca Benini (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2018)

Design and Evaluation of a Low-Power Sensor Device for Induced Rockfall Experiments. - Andrin Caviezel; Michael Schaffner; Lukas Cavigelli; Pascal Niklaus; Yves Bühler; Perry Bartelt; Michele Magno; Luca Benini (IEEE Trans. Instrum. Meas., 2018)

Towards Edge-Aware Spatio-Temporal Filtering in Real-Time. - Michael Schaffner; Florian Scheidegger; Lukas Cavigelli; Hubert Kaeslin; Luca Benini; Aljosa Smolic (IEEE Trans. Image Process., 2018)

Extended Bit-Plane Compression for Convolutional Neural Network Accelerators. - Lukas Cavigelli; Luca Benini (AICAS, 2019)

Laelaps: An Energy-Efficient Seizure Detection Algorithm from Long-term Human iEEG Recordings without False Alarms. - Alessio Burrello; Lukas Cavigelli; Kaspar Schindler; Luca Benini; Abbas Rahimi (DATE, 2019)

FANNCortexM: An Open Source Toolkit for Deployment of Multi-layer Neural Networks on ARM Cortex-M Family Microcontrollers : Performance Analysis with Stress Detection. - Michele Magno; Lukas Cavigelli; Philipp Mayer; Ferdinand von Hagen; Luca Benini (WF-IoT, 2019)

Additive Noise Annealing and Approximation Properties of Quantized Neural Networks. - Matteo Spallanzani; Lukas Cavigelli; Gian Paolo Leonardi; Marko Bertogna; Luca Benini (CoRR, 2019)

HR-SAR-Net: A Deep Neural Network for Urban Scene Segmentation from High-Resolution SAR Data. - Xiaying Wang; Lukas Cavigelli; Manuel Eggimann; Michele Magno; Luca Benini (CoRR, 2019)

Hyperdrive: A Multi-Chip Systolically Scalable Binary-Weight CNN Inference Engine. - Renzo Andri; Lukas Cavigelli; Davide Rossi; Luca Benini (IEEE J. Emerg. Sel. Topics Circuits Syst., 2019)

EBPC: Extended Bit-Plane Compression for Deep Neural Network Inference and Training Accelerators. - Lukas Cavigelli; Georg Rutishauser; Luca Benini (IEEE J. Emerg. Sel. Topics Circuits Syst., 2019)

SmarTEG: An Autonomous Wireless Sensor Node for High Accuracy Accelerometer-Based Monitoring. - Michele Magno; Lukas Sigrist; Andres Gomez 001; Lukas Cavigelli; Antonio Libri; Emanuel M. Popovici; Luca Benini (Sensors, 2019)

Towards energy-efficient convolutional neural network inference. - Lukas Cavigelli (Hartung-Gorre Verlag, 2019)

InfiniWolf: Energy Efficient Smart Bracelet for Edge Computing with Dual Source Energy Harvesting. - Michele Magno; Xiaying Wang; Manuel Eggimann; Lukas Cavigelli; Luca Benini (DATE, 2020)

Sound event detection with binary neural networks on tightly power-constrained IoT devices. - Gianmarco Cerutti; Renzo Andri; Lukas Cavigelli; Elisabetta Farella; Michele Magno; Luca Benini (ISLPED, 2020)

Q-EEGNet: an Energy-Efficient 8-bit Quantized Parallel EEGNet Implementation for Edge Motor-Imagery Brain-Machine Interfaces. - Tibor Schneider; Xiaying Wang; Michael Hersche; Lukas Cavigelli; Luca Benini (SMARTCOMP, 2020)

EEG-TCNet: An Accurate Temporal Convolutional Network for Embedded Motor-Imagery Brain-Machine Interfaces. - Thorir Mar Ingolfsson; Michael Hersche; Xiaying Wang; Nobuaki Kobayashi; Lukas Cavigelli; Luca Benini (SMC, 2020)

RPR: Random Partition Relaxation for Training; Binary and Ternary Weight Neural Networks. - Lukas Cavigelli; Luca Benini (CoRR, 2020)

FANN-on-MCU: An Open-Source Toolkit for Energy-Efficient Neural Network Inference at the Edge of the Internet of Things. - Xiaying Wang; Michele Magno; Lukas Cavigelli; Luca Benini (IEEE Internet Things J., 2020)

CBinfer: Exploiting Frame-to-Frame Locality for Faster Convolutional Network Inference on Video Streams. - Lukas Cavigelli; Luca Benini (IEEE Trans. Circuits Syst. Video Technol., 2020)

ECG-TCN: Wearable Cardiac Arrhythmia Detection with a Temporal Convolutional Network. - Thorir Mar Ingolfsson; Xiaying Wang; Michael Hersche; Alessio Burrello; Lukas Cavigelli; Luca Benini (AICAS, 2021)

Late Breaking Results: Reinforcement Learning for Scalable Logic Optimization with Graph Neural Networks. - Xavier Timoneda; Lukas Cavigelli (DAC, 2021)

ChewBaccaNN: A Flexible 223 TOPS/W BNN Accelerator. - Renzo Andri; Geethan Karunaratne; Lukas Cavigelli; Luca Benini (ISCAS, 2021)

Mixed-Precision Quantization and Parallel Implementation of Multispectral Riemannian Classification for Brain-Machine Interfaces. - Xiaying Wang; Tibor Schneider; Michael Hersche; Lukas Cavigelli; Luca Benini (ISCAS, 2021)

Reinforcement Learning for Scalable Logic Optimization with Graph Neural Networks. - Xavier Timoneda; Lukas Cavigelli (CoRR, 2021)

Sub-100 $ mu$W Multispectral Riemannian Classification for EEG-Based Brain-Machine Interfaces. - Xiaying Wang; Lukas Cavigelli; Tibor Schneider; Luca Benini (IEEE Trans. Biomed. Circuits Syst., 2021)

Towards On-device Domain Adaptation for Noise-Robust Keyword Spotting. - Cristian Cioflan; Lukas Cavigelli; Manuele Rusci; Miguel de Prado; Luca Benini (AICAS, 2022)

A "New Ara" for Vector Computing: An Open Source Highly Efficient RISC-V V 1.0 Vector Processor Design. - Matteo Perotti; Matheus A. Cavalcante; Nils Wistoff; Renzo Andri; Lukas Cavigelli; Luca Benini (ASAP, 2022)

Going Further With Winograd Convolutions: Tap-Wise Quantization for Efficient Inference on 4x4 Tiles. - Renzo Andri; Beatrice Bussolino; Antonio Cipolletta; Lukas Cavigelli; Zhe Wang 023 (MICRO, 2022)

Going Further With Winograd Convolutions: Tap-Wise Quantization for Efficient Inference on 4x4 Tile. - Renzo Andri; Beatrice Bussolino; Antonio Cipolletta; Lukas Cavigelli; Zhe Wang 023 (CoRR, 2022)

CUTIE: Beyond PetaOp/s/W Ternary DNN Inference Acceleration With Better-Than-Binary Energy Efficiency. - Moritz Scherer 001; Georg Rutishauser; Lukas Cavigelli; Luca Benini (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2022)

Sub-mW Keyword Spotting on an MCU: Analog Binary Feature Extraction and Binary Neural Networks. - Gianmarco Cerutti; Lukas Cavigelli; Renzo Andri; Michele Magno; Elisabetta Farella; Luca Benini (IEEE Trans. Circuits Syst. I Regul. Pap., 2022)

Vau Da Muntanialas: Energy-Efficient Multi-Die Scalable Acceleration of RNN Inference. - Gianna Paulin; Francesco Conti 001; Lukas Cavigelli; Luca Benini (IEEE Trans. Circuits Syst. I Regul. Pap., 2022)

Flex-SFU: Accelerating DNN Activation Functions by Non-Uniform Piecewise Approximation. - Enrico Reggiani; Renzo Andri; Lukas Cavigelli (DAC, 2023)

RL-based Stateful Neural Adaptive Sampling and Denoising for Real-Time Path Tracing. - Antoine Scardigli; Lukas Cavigelli; Lorenz K. Müller (NeurIPS, 2023)

ReDSEa: Automated Acceleration of Triangular Solver on Supercloud Heterogeneous Systems. - Georgios Zacharopoulos; Ilias Bournias; Verner Vlacic; Lukas Cavigelli (CoRR, 2023)

Ara2: Exploring Single- and Multi-Core Vector Processing with an Efficient RVV1.0 Compliant Open-Source Processor. - Matteo Perotti; Matheus A. Cavalcante; Renzo Andri; Lukas Cavigelli; Luca Benini (CoRR, 2023)

Stella Nera: Achieving 161 TOp/s/W with Multiplier-free DNN Acceleration based on Approximate Matrix Multiplication. - Jannis Schönleber; Lukas Cavigelli; Renzo Andri; Matteo Perotti; Luca Benini (CoRR, 2023)

Efficient Inference With Model Cascades. - Luzian Lebovitz; Lukas Cavigelli; Michele Magno; Lorenz K. Müller (Trans. Mach. Learn. Res., 2023)

On-Device Domain Learning for Keyword Spotting on Low-Power Extreme Edge Embedded Systems. - Cristian Cioflan; Lukas Cavigelli; Manuele Rusci; Miguel de Prado; Luca Benini (AICAS, 2024)

Deep Recommender Models Inference: Automatic Asymmetric Data Flow Optimization. - Giuseppe Ruggeri; Renzo Andri; Daniele Jahier Pagliari; Lukas Cavigelli (ICCD, 2024)

Boosting keyword spotting through on-device learnable user speech characteristics. - Cristian Cioflan; Lukas Cavigelli; Luca Benini (CoRR, 2024)

Ascend-CC: Confidential Computing on Heterogeneous NPU for Emerging Generative AI Workloads. - Aritra Dhar; Clément Thorens; Lara Magdalena Lazier; Lukas Cavigelli (CoRR, 2024)

AcceLLM: Accelerating LLM Inference using Redundancy for Load Balancing and Data Locality. - Ilias Bournias; Lukas Cavigelli; Georgios Zacharopoulos (CoRR, 2024)

SSSD: Simply-Scalable Speculative Decoding. - Michele Marzollo; Jiawei Zhuang; Niklas Roemer; Lorenz K. Müller; Lukas Cavigelli (CoRR, 2024)

Introduction to the Special Issue on tinyML. - Theocharis Theocharides; Charlotte Frenkel; Lukas Cavigelli (ACM Trans. Embed. Comput. Syst., 2024)

Ara2: Exploring Single- and Multi-Core Vector Processing With an Efficient RVV 1.0 Compliant Open-Source Processor. - Matteo Perotti; Matheus A. Cavalcante; Renzo Andri; Lukas Cavigelli; Luca Benini (IEEE Trans. Computers, 2024)

Stella Nera: A Differentiable Maddness-Based Hardware Accelerator for Efficient Approximate Matrix Multiplication. - Jannis Schönleber; Lukas Cavigelli; Matteo Perotti; Luca Benini; Renzo Andri (ISVLSI, 2025)

Guardain: Protecting Emerging Generative AI Workloads on Heterogeneous NPU. - Aritra Dhar; Clément Thorens; Lara Magdalena Lazier; Lukas Cavigelli (SP, 2025)

PRESERVE: Prefetching Model Weights and KV-Cache in Distributed LLM Serving. - Ahmet Caner Yüzügüler; Jiawei Zhuang; Lukas Cavigelli (CoRR, 2025)

Top-Theta Attention: Sparsifying Transformers by Compensated Thresholding. - Konstantin Berestizshevsky; Renzo Andri; Lukas Cavigelli (CoRR, 2025)

Late Breaking Results: The Art of Beating the Odds with Predictor-Guided Random Design Space Exploration. - Felix Arnold; Maxence Bouvier; Ryan Amaudruz; Renzo Andri; Lukas Cavigelli (CoRR, 2025)

AC-LoRA: (Almost) Training-Free Access Control-Aware Multi-Modal LLMs. - Lara Magdalena Lazier; Aritra Dhar; Vasilije Stambolic; Lukas Cavigelli (CoRR, 2025)

Explicit Sign-Magnitude Encoders Enable Power-Efficient Multipliers. - Felix Arnold; Maxence Bouvier; Ryan Amaudruz; Renzo Andri; Lukas Cavigelli (CoRR, 2025)

GENIAL: Generative Design Space Exploration via Network Inversion for Low Power Algorithmic Logic Units. - Maxence Bouvier; Ryan Amaudruz; Felix Arnold; Renzo Andri; Lukas Cavigelli (CoRR, 2025)