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Found 9 papers, 5 papers with code
MP-DPD: Low-Complexity Mixed-Precision Neural Networks for Energy-Efficient Digital Predistortion of Wideband Power Amplifiers
Applied to a 160MHz-BW 1024-QAM OFDM signal from a digital RF PA, MP-DPD gives no performance loss against 32-bit floating-point precision DPDs, while achieving -43. 75 (L)/-45. 27 (R) dBc in Adjacent Channel Power Ratio (ACPR) and -38. 72 dB in Error Vector Magnitude (EVM).
Event-Based Eye Tracking. AIS 2024 Challenge Survey
This survey reviews the AIS 2024 Event-Based Eye Tracking (EET) Challenge.
Retrieval-based Full-length Wikipedia Generation for Emergent Events
In today's fast-paced world, the growing demand to quickly generate comprehensive and accurate Wikipedia documents for emerging events is both crucial and challenging.
Selecting Large Language Model to Fine-tune via Rectified Scaling Law
The ever-growing ecosystem of LLMs has posed a challenge in selecting the most appropriate pre-trained model to fine-tune amidst a sea of options.
Epilepsy Seizure Detection and Prediction using an Approximate Spiking Convolutional Transformer
Epilepsy is a common disease of the nervous system.
3ET: Efficient Event-based Eye Tracking using a Change-Based ConvLSTM Network
This paper presents a sparse Change-Based Convolutional Long Short-Term Memory (CB-ConvLSTM) model for event-based eye tracking, key for next-generation wearable healthcare technology such as AR/VR headsets.
To Spike or Not To Spike: A Digital Hardware Perspective on Deep Learning Acceleration
The power efficiency of the biological brain outperforms any large-scale deep learning ( DL ) model; thus, neuromorphic computing tries to mimic the brain operations, such as spike-based information processing, to improve the efficiency of DL models.
Skydiver: A Spiking Neural Network Accelerator Exploiting Spatio-Temporal Workload Balance
Spiking Neural Networks (SNNs) are developed as a promising alternative to Artificial Neural networks (ANNs) due to their more realistic brain-inspired computing models.
Domain Adaptation via Maximizing Surrogate Mutual Information
In the framework, a surrogate joint distribution models the underlying joint distribution of the unlabeled target domain.
