“Alissa Hattman’s Sift is gorgeous, fierce, and wise. In this dystopian, woman-centric landscape, the boundaries between internal and external reality are shimmeringly porous, and heartbreak and magic …

Here you will find invitations to engage with Alissa Hattman’s Sift from different and intersecting vantages. The contributors are writers, artists, teachers, scholars, community leaders, and activists.

Alissa Hattman’s Sift is an extraordinarily palpable rendition of how love and grief might be reshaped by our still-unfolding climate crisis.

This means more work for us as we have to sift through low quality submissions. Because of this, before putting ergot. on a list or newsletter, we ask that you first contact us to ask permission at …

May 4, 2023 · From tech company employees who’d like to sift through users’ messages, looking for someone they can turn in for a bounty. To show that Democratic lawmakers really care about …

As the context size increases with the built-in recurrence, the system identifies and corrects its own errors. Our approach yields state-of-the-art performance on both the Stanford Background Dataset …

Various descriptors such as SIFT (Lowe, 2004) and HOG (Dalal & Triggs, 2005) offer a more robust representation, and have been highly successful in many computer vision applications.

As the context size increases with the built-in recurrence, the system identifies and cor-rects its own errors. Our approach yields state-of-the-art performance on both the Stanford Back-ground Dataset …

Based on this, we propose a gradient-based sparse fine-tuning algorithm, named $\textbf {S}$parse $\textbf {I}$ncrement $\textbf {F}$ine-$\textbf {T}$uning (SIFT), and validate its effectiveness on a …

Thus a crit-ical challenge for automatic scene recognition lies in the semantic gap between the low-level image features, such as the local gradient-based SIFT and HOG features (Lowe, 2004; Dalal & …