SC2GAN: Rethinking Entanglement by Self-correcting Correlated GAN Space

Generative Adversarial Networks (GANs) can synthesize realistic images, with the learned latent space shown to encode rich semantic information with various interpretable directions. However, due to the unstructured nature of the learned latent space, it inherits the bias from the training data where specific groups of visual attributes that are not causally related tend to appear together, a phenomenon also known as spurious correlations, e.g., age and eyeglasses or women and lipsticks. Consequently, the learned distribution often lacks the proper modelling of the missing examples. The interpolation following editing directions for one attribute could result in entangled changes with other attributes. To address this problem, previous works typically adjust the learned directions to minimize the changes in other attributes, yet they still fail on strongly correlated features. In this work, we study the entanglement issue in both the training data and the learned latent space for the StyleGAN2-FFHQ model. We propose a novel framework SC$^2$GAN that achieves disentanglement by re-projecting low-density latent code samples in the original latent space and correcting the editing directions based on both the high-density and low-density regions. By leveraging the original meaningful directions and semantic region-specific layers, our framework interpolates the original latent codes to generate images with attribute combination that appears infrequently, then inverts these samples back to the original latent space. We apply our framework to pre-existing methods that learn meaningful latent directions and showcase its strong capability to disentangle the attributes with small amounts of low-density region samples added.Comment: Accepted to the Out Of Distribution Generalization in Computer Vision workshop at ICCV202

Bromide-assisted chemoselective Heck reaction of 3-bromoindazoles under high-speed ball-milling conditions: synthesis of axitinib

A mechanically-activated chemoselective Heck coupling for the synthesis of 3-vinylindazoles has been developed with the aid of catalytic amounts of TBAB and NaBr as both dehalogenation restrainer and grinding auxiliary. After tuning of the chemical conditions and mechanical parameters, a series of non-activated 3-bromoindazoles and a broad scope of olefins worked well to give the corresponding coupling products in good to excellent yields. A further application of this protocol was performed in a two-step mechanochemical Heck/Migita cross coupling, which provided a highly efficient route for the synthesis of axitinib

A Jurassic wood providing insights into the earliest step in Ginkgo wood evolution

International audienceThe fossil record of Ginkgo leaf and reproductive organs has been well dated to the Mid-Jurassic (170 Myr). However, the fossil wood record that can safely be assigned to Ginkgoales has not yet been reported from strata predating the late Early Cretaceous (ca. 100 Myr). Here, we report a new fossil wood from the Mid-Late Jurassic transition deposit (153–165 Myr) of northeastern China. The new fossil wood specimen displays several Ginkgo features, including inflated axial parenchyma and intrusive tracheid tips. Because it is only slightly younger than the oldest recorded Ginkgo reproductive organs (the Yima Formation, 170 Myr), this fossil wood very probably represents the oldest bona fide fossil Ginkgo wood and the missing ancestral form of Ginkgo wood evolution

New record of fossil wood Xenoxylon from the Late Triassic in the Sichuan Basin, southern China and its paleoclimatic implications

International audienc