- Elements of Causal Inference by Jonas Peters, Dominik Janzing, and Bernhard Schölkopf
- Linear Regression Analysis by George A. F. Seber and Alan J. Lee
- Deep Learning by Ian Goodfellow, Yoshua Bengio, and Aaron Courville
- Duality, a medley of sources
- Stochastic Differential Equations by Bernt Øksendal
While they're not textbooks, I also strongly recommend Sinho Chewi's Theoretical Statistics notes. Those follow most of Theoretical Statistics by Robert W. Keener and parts of Asymptotic Statistics by A. W. van der Vaart for Berkeley courses 210A and 210B, respectively.