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20162026
most citedThe local backward heat problem

5 citations · 9 across the 23 of their papers we have counts for

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Showing 2026Show all

7 papers · 1 filter

math.RA2026

Automorphic Transcendence Degree, Growth, and Skew Normalization

Dinh Van Hoang, Vo Ngoc Thieu, Phan Thanh Toan

We study automorphic transcendence degree for quotients of multivariate skew polynomial rings over a division ring D. We identify this invariant with relative growth dimension, the…

math.AC2026

A one-dimensional coherent domain with non-Prüfer integral closure

Viet-Hoang Tran, Thieu N. Vo, Tan M. Nguyen

In a question recorded in 1978, Vasconcelos asked whether the integral closure of a one-dimensional coherent local domain in its fraction field is Prüfer. We construct such a domai…

math.AC2026

Dimensions of a ring and its formal power series ring

Viet-Hoang Tran, Thieu N. Vo, Tan M. Nguyen

Understanding the relation between and is a classical problem in commutative algebra. For a Noetherian ring , one has , but the gene…

math.AC2026

Bouvier's Conjecture and Dimension Sequences of Unique Factorization Domains

Viet-Hoang Tran, Thieu N. Vo, Tan M. Nguyen

We prove Bouvier's conjecture. More generally, an integer sequence with is realized by a unique factorization domain (UFD) with $\dim R[X_1,\ldo…

math.AC2026

Polynomial extensions do not preserve the strong finite type property

Viet-Hoang Tran, Phan Thanh Toan, Thieu N. Vo +1

Arnold introduced the strong finite type (SFT) property in 1973 while studying the dimension of power series rings. For several classes of rings, polynomial extension is known to p…

math.AC2026

The Noetherian Case of Bayart's Power-Series Question

Viet-Hoang Tran, Dung V. Nguyen, Quang X. Nguyen +2

Let be a commutative Noetherian ring. We prove that if the one-variable formal power-series ring is a unique factorization domain, then so is the two-variable formal p…

cs.LG2026

MuonSSM: Orthogonalizing State Space Models for Sequence Modeling

Thai-Khanh Nguyen, Ngoc-Bich-Uyen Vo, Thieu N. Vo +2

State space models (SSMs) have emerged as efficient linear-time alternatives to attention for long-sequence modeling. However, existing SSMs often suffer from instability and memor…