1 citations · 1 across the 6 of their papers we have counts for
7 papers
Raven: High-Recall Sequence Modeling with Sparse Memory Routing
Arshia Afzal, Aviv Bick, Eric P. Xing +2
Long-context recall in linear-time sequence models highlights a tradeoff in how they write to memory. State-based linear models, such as state-space models (SSMs) and linear Transf…
Spatial Priors via Space Filling Curves for Small and Limited Data Vision Transformers
Leyla Naz Candogan, Arshia Afzal, Pol Puigdemont +1
Though Vision Transformers (ViTs) have become the dominant backbone in many computer vision tasks, due to permutation equivariance, their attention mechanism lacks explicit spatial…
Selective Rotary Position Embedding
Sajad Movahedi, Timur Carstensen, Arshia Afzal +3
Position information is essential for language modeling. In softmax transformers, Rotary Position Embeddings (\textit{RoPE}) encode positions through \textit{fixed-angle} rotations…
MT-NAM: An Efficient and Adaptive Model for Epileptic Seizure Detection
Arshia Afzal, Volkan Cevher, Mahsa Shoaran
Enhancing the accuracy and efficiency of machine learning algorithms employed in neural interface systems is crucial for advancing next-generation intelligent therapeutic devices.…
Linear Attention for Efficient Bidirectional Sequence Modeling
Arshia Afzal, Elias Abad Rocamora, Leyla Naz Candogan +5
Linear Transformers and State Space Models have emerged as efficient alternatives to softmax Transformers for causal sequence modeling, enabling parallel training via matrix multip…
REST: Efficient and Accelerated EEG Seizure Analysis through Residual State Updates
Arshia Afzal, Grigorios Chrysos, Volkan Cevher +1
EEG-based seizure detection models face challenges in terms of inference speed and memory efficiency, limiting their real-time implementation in clinical devices. This paper introd…
Challenges and Opportunities of Edge AI for Next-Generation Implantable BMIs
MohammadAli Shaeri, Arshia Afzal, Mahsa Shoaran
Neuroscience and neurotechnology are currently being revolutionized by artificial intelligence (AI) and machine learning. AI is widely used to study and interpret neural signals (a…